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Key Responsibilities
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Essential Skills - What You'll Bring
• Proven experience in data engineering, platform engineering, site reliability engineering, DataOps, or a closely related role focused on data platform reliability and operations.
• Strong hands-on experience with Azure-based data platforms, particularly Azure Databricks and core Azure data services such as Data Lake Storage, Data Factory/Synapse, and analytical stores, with familiarity of equivalent services in AWS.
• Strong understanding of modern data platform architectures, including data lakes, warehouses or lakehouses, orchestration frameworks, transformation pipelines, streaming services, and analytical consumption layers.
• Experience designing and implementing monitoring, observability, logging, alerting, and incident management approaches for Databricks workloads and Azure data services, using tools such as Azure Monitor, Log Analytics, or similar.
• Strong understanding of data quality, reconciliation, validation, and lineage concepts, and practical experience implementing control frameworks that protect critical data flows and products.
• Hands-on experience with Azure Purview or comparable data cataloge and lineage tooling, including configuration of collections, classification, ownership, and lineage for key datasets.
• Good understanding of reliability engineering principles such as availability targets, resilience patterns, recoverability, service health indicators, and operational readiness assessments.
• Experience using scripting and automation (for example, Python, PowerShell, or similar) to remove operational toil, improve repeatability, and strengthen recovery and deployment processes.
• Ability to diagnose and resolve complex issues that span data pipelines, integrations, cloud infrastructure, configuration, and source or downstream systems, and to drive pragmatic remediation.
• Strong collaboration and communication skills, with the ability to work effectively across data engineering, architecture, cloud platform, security, delivery, and operational teams, and to explain issues and trade-offs clearly to technical and non-technical stakeholders.
• Experience with Azure-native observability tooling and patterns for Databricks and the wider Azure data stack, and exposure to equivalent AWS monitoring approaches.
Desirable Skills - What Makes You Stand Out
• Experience tuning and optimising Databricks jobs, clusters, and workflows for performance, cost efficiency, and reliability in production environments.
• Familiarity with CI/CD practices, infrastructure as code, and automated testing for data platforms, supporting safe, repeatable, and low-risk changes to data services.
• Experience working in regulated or contractually governed environments such as public sector, health, employment services, or similarly controlled industries, where se...
....Read more...
Type: Permanent Location: Reno, US-NV
Salary / Rate: Not Specified
Posted: 2026-06-04 08:36:12
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Key Responsibilities
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Essential Skills - What You'll Bring
• Proven experience in data engineering, platform engineering, site reliability engineering, DataOps, or a closely related role focused on data platform reliability and operations.
• Strong hands-on experience with Azure-based data platforms, particularly Azure Databricks and core Azure data services such as Data Lake Storage, Data Factory/Synapse, and analytical stores, with familiarity of equivalent services in AWS.
• Strong understanding of modern data platform architectures, including data lakes, warehouses or lakehouses, orchestration frameworks, transformation pipelines, streaming services, and analytical consumption layers.
• Experience designing and implementing monitoring, observability, logging, alerting, and incident management approaches for Databricks workloads and Azure data services, using tools such as Azure Monitor, Log Analytics, or similar.
• Strong understanding of data quality, reconciliation, validation, and lineage concepts, and practical experience implementing control frameworks that protect critical data flows and products.
• Hands-on experience with Azure Purview or comparable data cataloge and lineage tooling, including configuration of collections, classification, ownership, and lineage for key datasets.
• Good understanding of reliability engineering principles such as availability targets, resilience patterns, recoverability, service health indicators, and operational readiness assessments.
• Experience using scripting and automation (for example, Python, PowerShell, or similar) to remove operational toil, improve repeatability, and strengthen recovery and deployment processes.
• Ability to diagnose and resolve complex issues that span data pipelines, integrations, cloud infrastructure, configuration, and source or downstream systems, and to drive pragmatic remediation.
• Strong collaboration and communication skills, with the ability to work effectively across data engineering, architecture, cloud platform, security, delivery, and operational teams, and to explain issues and trade-offs clearly to technical and non-technical stakeholders.
• Experience with Azure-native observability tooling and patterns for Databricks and the wider Azure data stack, and exposure to equivalent AWS monitoring approaches.
Desirable Skills - What Makes You Stand Out
• Experience tuning and optimising Databricks jobs, clusters, and workflows for performance, cost efficiency, and reliability in production environments.
• Familiarity with CI/CD practices, infrastructure as code, and automated testing for data platforms, supporting safe, repeatable, and low-risk changes to data services.
• Experience working in regulated or contractually governed environments such as public sector, health, employment services, or similarly controlled industries, where se...
....Read more...
Type: Permanent Location: Omaha, US-NE
Salary / Rate: Not Specified
Posted: 2026-06-04 08:36:11
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Key Responsibilities
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Essential Skills - What You'll Bring
• Proven experience in data engineering, platform engineering, site reliability engineering, DataOps, or a closely related role focused on data platform reliability and operations.
• Strong hands-on experience with Azure-based data platforms, particularly Azure Databricks and core Azure data services such as Data Lake Storage, Data Factory/Synapse, and analytical stores, with familiarity of equivalent services in AWS.
• Strong understanding of modern data platform architectures, including data lakes, warehouses or lakehouses, orchestration frameworks, transformation pipelines, streaming services, and analytical consumption layers.
• Experience designing and implementing monitoring, observability, logging, alerting, and incident management approaches for Databricks workloads and Azure data services, using tools such as Azure Monitor, Log Analytics, or similar.
• Strong understanding of data quality, reconciliation, validation, and lineage concepts, and practical experience implementing control frameworks that protect critical data flows and products.
• Hands-on experience with Azure Purview or comparable data cataloge and lineage tooling, including configuration of collections, classification, ownership, and lineage for key datasets.
• Good understanding of reliability engineering principles such as availability targets, resilience patterns, recoverability, service health indicators, and operational readiness assessments.
• Experience using scripting and automation (for example, Python, PowerShell, or similar) to remove operational toil, improve repeatability, and strengthen recovery and deployment processes.
• Ability to diagnose and resolve complex issues that span data pipelines, integrations, cloud infrastructure, configuration, and source or downstream systems, and to drive pragmatic remediation.
• Strong collaboration and communication skills, with the ability to work effectively across data engineering, architecture, cloud platform, security, delivery, and operational teams, and to explain issues and trade-offs clearly to technical and non-technical stakeholders.
• Experience with Azure-native observability tooling and patterns for Databricks and the wider Azure data stack, and exposure to equivalent AWS monitoring approaches.
Desirable Skills - What Makes You Stand Out
• Experience tuning and optimising Databricks jobs, clusters, and workflows for performance, cost efficiency, and reliability in production environments.
• Familiarity with CI/CD practices, infrastructure as code, and automated testing for data platforms, supporting safe, repeatable, and low-risk changes to data services.
• Experience working in regulated or contractually governed environments such as public sector, health, employment services, or similarly controlled industries, where se...
....Read more...
Type: Permanent Location: Missoula, US-MT
Salary / Rate: Not Specified
Posted: 2026-06-04 08:36:10
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Key Responsibilities
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Essential Skills - What You'll Bring
• Proven experience in data engineering, platform engineering, site reliability engineering, DataOps, or a closely related role focused on data platform reliability and operations.
• Strong hands-on experience with Azure-based data platforms, particularly Azure Databricks and core Azure data services such as Data Lake Storage, Data Factory/Synapse, and analytical stores, with familiarity of equivalent services in AWS.
• Strong understanding of modern data platform architectures, including data lakes, warehouses or lakehouses, orchestration frameworks, transformation pipelines, streaming services, and analytical consumption layers.
• Experience designing and implementing monitoring, observability, logging, alerting, and incident management approaches for Databricks workloads and Azure data services, using tools such as Azure Monitor, Log Analytics, or similar.
• Strong understanding of data quality, reconciliation, validation, and lineage concepts, and practical experience implementing control frameworks that protect critical data flows and products.
• Hands-on experience with Azure Purview or comparable data cataloge and lineage tooling, including configuration of collections, classification, ownership, and lineage for key datasets.
• Good understanding of reliability engineering principles such as availability targets, resilience patterns, recoverability, service health indicators, and operational readiness assessments.
• Experience using scripting and automation (for example, Python, PowerShell, or similar) to remove operational toil, improve repeatability, and strengthen recovery and deployment processes.
• Ability to diagnose and resolve complex issues that span data pipelines, integrations, cloud infrastructure, configuration, and source or downstream systems, and to drive pragmatic remediation.
• Strong collaboration and communication skills, with the ability to work effectively across data engineering, architecture, cloud platform, security, delivery, and operational teams, and to explain issues and trade-offs clearly to technical and non-technical stakeholders.
• Experience with Azure-native observability tooling and patterns for Databricks and the wider Azure data stack, and exposure to equivalent AWS monitoring approaches.
Desirable Skills - What Makes You Stand Out
• Experience tuning and optimising Databricks jobs, clusters, and workflows for performance, cost efficiency, and reliability in production environments.
• Familiarity with CI/CD practices, infrastructure as code, and automated testing for data platforms, supporting safe, repeatable, and low-risk changes to data services.
• Experience working in regulated or contractually governed environments such as public sector, health, employment services, or similarly controlled industries, where se...
....Read more...
Type: Permanent Location: Las Vegas, US-NV
Salary / Rate: Not Specified
Posted: 2026-06-04 08:36:10
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Key Responsibilities
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Essential Skills - What You'll Bring
• Proven experience in data engineering, platform engineering, site reliability engineering, DataOps, or a closely related role focused on data platform reliability and operations.
• Strong hands-on experience with Azure-based data platforms, particularly Azure Databricks and core Azure data services such as Data Lake Storage, Data Factory/Synapse, and analytical stores, with familiarity of equivalent services in AWS.
• Strong understanding of modern data platform architectures, including data lakes, warehouses or lakehouses, orchestration frameworks, transformation pipelines, streaming services, and analytical consumption layers.
• Experience designing and implementing monitoring, observability, logging, alerting, and incident management approaches for Databricks workloads and Azure data services, using tools such as Azure Monitor, Log Analytics, or similar.
• Strong understanding of data quality, reconciliation, validation, and lineage concepts, and practical experience implementing control frameworks that protect critical data flows and products.
• Hands-on experience with Azure Purview or comparable data cataloge and lineage tooling, including configuration of collections, classification, ownership, and lineage for key datasets.
• Good understanding of reliability engineering principles such as availability targets, resilience patterns, recoverability, service health indicators, and operational readiness assessments.
• Experience using scripting and automation (for example, Python, PowerShell, or similar) to remove operational toil, improve repeatability, and strengthen recovery and deployment processes.
• Ability to diagnose and resolve complex issues that span data pipelines, integrations, cloud infrastructure, configuration, and source or downstream systems, and to drive pragmatic remediation.
• Strong collaboration and communication skills, with the ability to work effectively across data engineering, architecture, cloud platform, security, delivery, and operational teams, and to explain issues and trade-offs clearly to technical and non-technical stakeholders.
• Experience with Azure-native observability tooling and patterns for Databricks and the wider Azure data stack, and exposure to equivalent AWS monitoring approaches.
Desirable Skills - What Makes You Stand Out
• Experience tuning and optimising Databricks jobs, clusters, and workflows for performance, cost efficiency, and reliability in production environments.
• Familiarity with CI/CD practices, infrastructure as code, and automated testing for data platforms, supporting safe, repeatable, and low-risk changes to data services.
• Experience working in regulated or contractually governed environments such as public sector, health, employment services, or similarly controlled industries, where se...
....Read more...
Type: Permanent Location: Springfield, US-MO
Salary / Rate: Not Specified
Posted: 2026-06-04 08:36:09
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Key Responsibilities
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Essential Skills - What You'll Bring
• Proven experience in data engineering, platform engineering, site reliability engineering, DataOps, or a closely related role focused on data platform reliability and operations.
• Strong hands-on experience with Azure-based data platforms, particularly Azure Databricks and core Azure data services such as Data Lake Storage, Data Factory/Synapse, and analytical stores, with familiarity of equivalent services in AWS.
• Strong understanding of modern data platform architectures, including data lakes, warehouses or lakehouses, orchestration frameworks, transformation pipelines, streaming services, and analytical consumption layers.
• Experience designing and implementing monitoring, observability, logging, alerting, and incident management approaches for Databricks workloads and Azure data services, using tools such as Azure Monitor, Log Analytics, or similar.
• Strong understanding of data quality, reconciliation, validation, and lineage concepts, and practical experience implementing control frameworks that protect critical data flows and products.
• Hands-on experience with Azure Purview or comparable data cataloge and lineage tooling, including configuration of collections, classification, ownership, and lineage for key datasets.
• Good understanding of reliability engineering principles such as availability targets, resilience patterns, recoverability, service health indicators, and operational readiness assessments.
• Experience using scripting and automation (for example, Python, PowerShell, or similar) to remove operational toil, improve repeatability, and strengthen recovery and deployment processes.
• Ability to diagnose and resolve complex issues that span data pipelines, integrations, cloud infrastructure, configuration, and source or downstream systems, and to drive pragmatic remediation.
• Strong collaboration and communication skills, with the ability to work effectively across data engineering, architecture, cloud platform, security, delivery, and operational teams, and to explain issues and trade-offs clearly to technical and non-technical stakeholders.
• Experience with Azure-native observability tooling and patterns for Databricks and the wider Azure data stack, and exposure to equivalent AWS monitoring approaches.
Desirable Skills - What Makes You Stand Out
• Experience tuning and optimising Databricks jobs, clusters, and workflows for performance, cost efficiency, and reliability in production environments.
• Familiarity with CI/CD practices, infrastructure as code, and automated testing for data platforms, supporting safe, repeatable, and low-risk changes to data services.
• Experience working in regulated or contractually governed environments such as public sector, health, employment services, or similarly controlled industries, where se...
....Read more...
Type: Permanent Location: Kansas City, US-MO
Salary / Rate: Not Specified
Posted: 2026-06-04 08:36:09
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Key Responsibilities
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Essential Skills - What You'll Bring
• Proven experience in data engineering, platform engineering, site reliability engineering, DataOps, or a closely related role focused on data platform reliability and operations.
• Strong hands-on experience with Azure-based data platforms, particularly Azure Databricks and core Azure data services such as Data Lake Storage, Data Factory/Synapse, and analytical stores, with familiarity of equivalent services in AWS.
• Strong understanding of modern data platform architectures, including data lakes, warehouses or lakehouses, orchestration frameworks, transformation pipelines, streaming services, and analytical consumption layers.
• Experience designing and implementing monitoring, observability, logging, alerting, and incident management approaches for Databricks workloads and Azure data services, using tools such as Azure Monitor, Log Analytics, or similar.
• Strong understanding of data quality, reconciliation, validation, and lineage concepts, and practical experience implementing control frameworks that protect critical data flows and products.
• Hands-on experience with Azure Purview or comparable data cataloge and lineage tooling, including configuration of collections, classification, ownership, and lineage for key datasets.
• Good understanding of reliability engineering principles such as availability targets, resilience patterns, recoverability, service health indicators, and operational readiness assessments.
• Experience using scripting and automation (for example, Python, PowerShell, or similar) to remove operational toil, improve repeatability, and strengthen recovery and deployment processes.
• Ability to diagnose and resolve complex issues that span data pipelines, integrations, cloud infrastructure, configuration, and source or downstream systems, and to drive pragmatic remediation.
• Strong collaboration and communication skills, with the ability to work effectively across data engineering, architecture, cloud platform, security, delivery, and operational teams, and to explain issues and trade-offs clearly to technical and non-technical stakeholders.
• Experience with Azure-native observability tooling and patterns for Databricks and the wider Azure data stack, and exposure to equivalent AWS monitoring approaches.
Desirable Skills - What Makes You Stand Out
• Experience tuning and optimising Databricks jobs, clusters, and workflows for performance, cost efficiency, and reliability in production environments.
• Familiarity with CI/CD practices, infrastructure as code, and automated testing for data platforms, supporting safe, repeatable, and low-risk changes to data services.
• Experience working in regulated or contractually governed environments such as public sector, health, employment services, or similarly controlled industries, where se...
....Read more...
Type: Permanent Location: St. Louis, US-MO
Salary / Rate: Not Specified
Posted: 2026-06-04 08:36:06
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Key Responsibilities
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Essential Skills - What You'll Bring
• Proven experience in data engineering, platform engineering, site reliability engineering, DataOps, or a closely related role focused on data platform reliability and operations.
• Strong hands-on experience with Azure-based data platforms, particularly Azure Databricks and core Azure data services such as Data Lake Storage, Data Factory/Synapse, and analytical stores, with familiarity of equivalent services in AWS.
• Strong understanding of modern data platform architectures, including data lakes, warehouses or lakehouses, orchestration frameworks, transformation pipelines, streaming services, and analytical consumption layers.
• Experience designing and implementing monitoring, observability, logging, alerting, and incident management approaches for Databricks workloads and Azure data services, using tools such as Azure Monitor, Log Analytics, or similar.
• Strong understanding of data quality, reconciliation, validation, and lineage concepts, and practical experience implementing control frameworks that protect critical data flows and products.
• Hands-on experience with Azure Purview or comparable data cataloge and lineage tooling, including configuration of collections, classification, ownership, and lineage for key datasets.
• Good understanding of reliability engineering principles such as availability targets, resilience patterns, recoverability, service health indicators, and operational readiness assessments.
• Experience using scripting and automation (for example, Python, PowerShell, or similar) to remove operational toil, improve repeatability, and strengthen recovery and deployment processes.
• Ability to diagnose and resolve complex issues that span data pipelines, integrations, cloud infrastructure, configuration, and source or downstream systems, and to drive pragmatic remediation.
• Strong collaboration and communication skills, with the ability to work effectively across data engineering, architecture, cloud platform, security, delivery, and operational teams, and to explain issues and trade-offs clearly to technical and non-technical stakeholders.
• Experience with Azure-native observability tooling and patterns for Databricks and the wider Azure data stack, and exposure to equivalent AWS monitoring approaches.
Desirable Skills - What Makes You Stand Out
• Experience tuning and optimising Databricks jobs, clusters, and workflows for performance, cost efficiency, and reliability in production environments.
• Familiarity with CI/CD practices, infrastructure as code, and automated testing for data platforms, supporting safe, repeatable, and low-risk changes to data services.
• Experience working in regulated or contractually governed environments such as public sector, health, employment services, or similarly controlled industries, where se...
....Read more...
Type: Permanent Location: Tupelo, US-MS
Salary / Rate: Not Specified
Posted: 2026-06-04 08:36:06
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Key Responsibilities
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Essential Skills - What You'll Bring
• Proven experience in data engineering, platform engineering, site reliability engineering, DataOps, or a closely related role focused on data platform reliability and operations.
• Strong hands-on experience with Azure-based data platforms, particularly Azure Databricks and core Azure data services such as Data Lake Storage, Data Factory/Synapse, and analytical stores, with familiarity of equivalent services in AWS.
• Strong understanding of modern data platform architectures, including data lakes, warehouses or lakehouses, orchestration frameworks, transformation pipelines, streaming services, and analytical consumption layers.
• Experience designing and implementing monitoring, observability, logging, alerting, and incident management approaches for Databricks workloads and Azure data services, using tools such as Azure Monitor, Log Analytics, or similar.
• Strong understanding of data quality, reconciliation, validation, and lineage concepts, and practical experience implementing control frameworks that protect critical data flows and products.
• Hands-on experience with Azure Purview or comparable data cataloge and lineage tooling, including configuration of collections, classification, ownership, and lineage for key datasets.
• Good understanding of reliability engineering principles such as availability targets, resilience patterns, recoverability, service health indicators, and operational readiness assessments.
• Experience using scripting and automation (for example, Python, PowerShell, or similar) to remove operational toil, improve repeatability, and strengthen recovery and deployment processes.
• Ability to diagnose and resolve complex issues that span data pipelines, integrations, cloud infrastructure, configuration, and source or downstream systems, and to drive pragmatic remediation.
• Strong collaboration and communication skills, with the ability to work effectively across data engineering, architecture, cloud platform, security, delivery, and operational teams, and to explain issues and trade-offs clearly to technical and non-technical stakeholders.
• Experience with Azure-native observability tooling and patterns for Databricks and the wider Azure data stack, and exposure to equivalent AWS monitoring approaches.
Desirable Skills - What Makes You Stand Out
• Experience tuning and optimising Databricks jobs, clusters, and workflows for performance, cost efficiency, and reliability in production environments.
• Familiarity with CI/CD practices, infrastructure as code, and automated testing for data platforms, supporting safe, repeatable, and low-risk changes to data services.
• Experience working in regulated or contractually governed environments such as public sector, health, employment services, or similarly controlled industries, where se...
....Read more...
Type: Permanent Location: Billings, US-MT
Salary / Rate: Not Specified
Posted: 2026-06-04 08:36:05
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Key Responsibilities
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Essential Skills - What You'll Bring
• Proven experience in data engineering, platform engineering, site reliability engineering, DataOps, or a closely related role focused on data platform reliability and operations.
• Strong hands-on experience with Azure-based data platforms, particularly Azure Databricks and core Azure data services such as Data Lake Storage, Data Factory/Synapse, and analytical stores, with familiarity of equivalent services in AWS.
• Strong understanding of modern data platform architectures, including data lakes, warehouses or lakehouses, orchestration frameworks, transformation pipelines, streaming services, and analytical consumption layers.
• Experience designing and implementing monitoring, observability, logging, alerting, and incident management approaches for Databricks workloads and Azure data services, using tools such as Azure Monitor, Log Analytics, or similar.
• Strong understanding of data quality, reconciliation, validation, and lineage concepts, and practical experience implementing control frameworks that protect critical data flows and products.
• Hands-on experience with Azure Purview or comparable data cataloge and lineage tooling, including configuration of collections, classification, ownership, and lineage for key datasets.
• Good understanding of reliability engineering principles such as availability targets, resilience patterns, recoverability, service health indicators, and operational readiness assessments.
• Experience using scripting and automation (for example, Python, PowerShell, or similar) to remove operational toil, improve repeatability, and strengthen recovery and deployment processes.
• Ability to diagnose and resolve complex issues that span data pipelines, integrations, cloud infrastructure, configuration, and source or downstream systems, and to drive pragmatic remediation.
• Strong collaboration and communication skills, with the ability to work effectively across data engineering, architecture, cloud platform, security, delivery, and operational teams, and to explain issues and trade-offs clearly to technical and non-technical stakeholders.
• Experience with Azure-native observability tooling and patterns for Databricks and the wider Azure data stack, and exposure to equivalent AWS monitoring approaches.
Desirable Skills - What Makes You Stand Out
• Experience tuning and optimising Databricks jobs, clusters, and workflows for performance, cost efficiency, and reliability in production environments.
• Familiarity with CI/CD practices, infrastructure as code, and automated testing for data platforms, supporting safe, repeatable, and low-risk changes to data services.
• Experience working in regulated or contractually governed environments such as public sector, health, employment services, or similarly controlled industries, where se...
....Read more...
Type: Permanent Location: Hattiesburg, US-MS
Salary / Rate: Not Specified
Posted: 2026-06-04 08:36:05
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Key Responsibilities
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Essential Skills - What You'll Bring
• Proven experience in data engineering, platform engineering, site reliability engineering, DataOps, or a closely related role focused on data platform reliability and operations.
• Strong hands-on experience with Azure-based data platforms, particularly Azure Databricks and core Azure data services such as Data Lake Storage, Data Factory/Synapse, and analytical stores, with familiarity of equivalent services in AWS.
• Strong understanding of modern data platform architectures, including data lakes, warehouses or lakehouses, orchestration frameworks, transformation pipelines, streaming services, and analytical consumption layers.
• Experience designing and implementing monitoring, observability, logging, alerting, and incident management approaches for Databricks workloads and Azure data services, using tools such as Azure Monitor, Log Analytics, or similar.
• Strong understanding of data quality, reconciliation, validation, and lineage concepts, and practical experience implementing control frameworks that protect critical data flows and products.
• Hands-on experience with Azure Purview or comparable data cataloge and lineage tooling, including configuration of collections, classification, ownership, and lineage for key datasets.
• Good understanding of reliability engineering principles such as availability targets, resilience patterns, recoverability, service health indicators, and operational readiness assessments.
• Experience using scripting and automation (for example, Python, PowerShell, or similar) to remove operational toil, improve repeatability, and strengthen recovery and deployment processes.
• Ability to diagnose and resolve complex issues that span data pipelines, integrations, cloud infrastructure, configuration, and source or downstream systems, and to drive pragmatic remediation.
• Strong collaboration and communication skills, with the ability to work effectively across data engineering, architecture, cloud platform, security, delivery, and operational teams, and to explain issues and trade-offs clearly to technical and non-technical stakeholders.
• Experience with Azure-native observability tooling and patterns for Databricks and the wider Azure data stack, and exposure to equivalent AWS monitoring approaches.
Desirable Skills - What Makes You Stand Out
• Experience tuning and optimising Databricks jobs, clusters, and workflows for performance, cost efficiency, and reliability in production environments.
• Familiarity with CI/CD practices, infrastructure as code, and automated testing for data platforms, supporting safe, repeatable, and low-risk changes to data services.
• Experience working in regulated or contractually governed environments such as public sector, health, employment services, or similarly controlled industries, where se...
....Read more...
Type: Permanent Location: Minneapolis, US-MN
Salary / Rate: Not Specified
Posted: 2026-06-04 08:36:04
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Key Responsibilities
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Essential Skills - What You'll Bring
• Proven experience in data engineering, platform engineering, site reliability engineering, DataOps, or a closely related role focused on data platform reliability and operations.
• Strong hands-on experience with Azure-based data platforms, particularly Azure Databricks and core Azure data services such as Data Lake Storage, Data Factory/Synapse, and analytical stores, with familiarity of equivalent services in AWS.
• Strong understanding of modern data platform architectures, including data lakes, warehouses or lakehouses, orchestration frameworks, transformation pipelines, streaming services, and analytical consumption layers.
• Experience designing and implementing monitoring, observability, logging, alerting, and incident management approaches for Databricks workloads and Azure data services, using tools such as Azure Monitor, Log Analytics, or similar.
• Strong understanding of data quality, reconciliation, validation, and lineage concepts, and practical experience implementing control frameworks that protect critical data flows and products.
• Hands-on experience with Azure Purview or comparable data cataloge and lineage tooling, including configuration of collections, classification, ownership, and lineage for key datasets.
• Good understanding of reliability engineering principles such as availability targets, resilience patterns, recoverability, service health indicators, and operational readiness assessments.
• Experience using scripting and automation (for example, Python, PowerShell, or similar) to remove operational toil, improve repeatability, and strengthen recovery and deployment processes.
• Ability to diagnose and resolve complex issues that span data pipelines, integrations, cloud infrastructure, configuration, and source or downstream systems, and to drive pragmatic remediation.
• Strong collaboration and communication skills, with the ability to work effectively across data engineering, architecture, cloud platform, security, delivery, and operational teams, and to explain issues and trade-offs clearly to technical and non-technical stakeholders.
• Experience with Azure-native observability tooling and patterns for Databricks and the wider Azure data stack, and exposure to equivalent AWS monitoring approaches.
Desirable Skills - What Makes You Stand Out
• Experience tuning and optimising Databricks jobs, clusters, and workflows for performance, cost efficiency, and reliability in production environments.
• Familiarity with CI/CD practices, infrastructure as code, and automated testing for data platforms, supporting safe, repeatable, and low-risk changes to data services.
• Experience working in regulated or contractually governed environments such as public sector, health, employment services, or similarly controlled industries, where se...
....Read more...
Type: Permanent Location: Marquette, US-MI
Salary / Rate: Not Specified
Posted: 2026-06-04 08:36:03
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Key Responsibilities
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Essential Skills - What You'll Bring
• Proven experience in data engineering, platform engineering, site reliability engineering, DataOps, or a closely related role focused on data platform reliability and operations.
• Strong hands-on experience with Azure-based data platforms, particularly Azure Databricks and core Azure data services such as Data Lake Storage, Data Factory/Synapse, and analytical stores, with familiarity of equivalent services in AWS.
• Strong understanding of modern data platform architectures, including data lakes, warehouses or lakehouses, orchestration frameworks, transformation pipelines, streaming services, and analytical consumption layers.
• Experience designing and implementing monitoring, observability, logging, alerting, and incident management approaches for Databricks workloads and Azure data services, using tools such as Azure Monitor, Log Analytics, or similar.
• Strong understanding of data quality, reconciliation, validation, and lineage concepts, and practical experience implementing control frameworks that protect critical data flows and products.
• Hands-on experience with Azure Purview or comparable data cataloge and lineage tooling, including configuration of collections, classification, ownership, and lineage for key datasets.
• Good understanding of reliability engineering principles such as availability targets, resilience patterns, recoverability, service health indicators, and operational readiness assessments.
• Experience using scripting and automation (for example, Python, PowerShell, or similar) to remove operational toil, improve repeatability, and strengthen recovery and deployment processes.
• Ability to diagnose and resolve complex issues that span data pipelines, integrations, cloud infrastructure, configuration, and source or downstream systems, and to drive pragmatic remediation.
• Strong collaboration and communication skills, with the ability to work effectively across data engineering, architecture, cloud platform, security, delivery, and operational teams, and to explain issues and trade-offs clearly to technical and non-technical stakeholders.
• Experience with Azure-native observability tooling and patterns for Databricks and the wider Azure data stack, and exposure to equivalent AWS monitoring approaches.
Desirable Skills - What Makes You Stand Out
• Experience tuning and optimising Databricks jobs, clusters, and workflows for performance, cost efficiency, and reliability in production environments.
• Familiarity with CI/CD practices, infrastructure as code, and automated testing for data platforms, supporting safe, repeatable, and low-risk changes to data services.
• Experience working in regulated or contractually governed environments such as public sector, health, employment services, or similarly controlled industries, where se...
....Read more...
Type: Permanent Location: Grand Rapids, US-MI
Salary / Rate: Not Specified
Posted: 2026-06-04 08:36:03
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Key Responsibilities
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Essential Skills - What You'll Bring
• Proven experience in data engineering, platform engineering, site reliability engineering, DataOps, or a closely related role focused on data platform reliability and operations.
• Strong hands-on experience with Azure-based data platforms, particularly Azure Databricks and core Azure data services such as Data Lake Storage, Data Factory/Synapse, and analytical stores, with familiarity of equivalent services in AWS.
• Strong understanding of modern data platform architectures, including data lakes, warehouses or lakehouses, orchestration frameworks, transformation pipelines, streaming services, and analytical consumption layers.
• Experience designing and implementing monitoring, observability, logging, alerting, and incident management approaches for Databricks workloads and Azure data services, using tools such as Azure Monitor, Log Analytics, or similar.
• Strong understanding of data quality, reconciliation, validation, and lineage concepts, and practical experience implementing control frameworks that protect critical data flows and products.
• Hands-on experience with Azure Purview or comparable data cataloge and lineage tooling, including configuration of collections, classification, ownership, and lineage for key datasets.
• Good understanding of reliability engineering principles such as availability targets, resilience patterns, recoverability, service health indicators, and operational readiness assessments.
• Experience using scripting and automation (for example, Python, PowerShell, or similar) to remove operational toil, improve repeatability, and strengthen recovery and deployment processes.
• Ability to diagnose and resolve complex issues that span data pipelines, integrations, cloud infrastructure, configuration, and source or downstream systems, and to drive pragmatic remediation.
• Strong collaboration and communication skills, with the ability to work effectively across data engineering, architecture, cloud platform, security, delivery, and operational teams, and to explain issues and trade-offs clearly to technical and non-technical stakeholders.
• Experience with Azure-native observability tooling and patterns for Databricks and the wider Azure data stack, and exposure to equivalent AWS monitoring approaches.
Desirable Skills - What Makes You Stand Out
• Experience tuning and optimising Databricks jobs, clusters, and workflows for performance, cost efficiency, and reliability in production environments.
• Familiarity with CI/CD practices, infrastructure as code, and automated testing for data platforms, supporting safe, repeatable, and low-risk changes to data services.
• Experience working in regulated or contractually governed environments such as public sector, health, employment services, or similarly controlled industries, where se...
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Type: Permanent Location: Duluth, US-MN
Salary / Rate: Not Specified
Posted: 2026-06-04 08:36:02
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Key Responsibilities
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Essential Skills - What You'll Bring
• Proven experience in data engineering, platform engineering, site reliability engineering, DataOps, or a closely related role focused on data platform reliability and operations.
• Strong hands-on experience with Azure-based data platforms, particularly Azure Databricks and core Azure data services such as Data Lake Storage, Data Factory/Synapse, and analytical stores, with familiarity of equivalent services in AWS.
• Strong understanding of modern data platform architectures, including data lakes, warehouses or lakehouses, orchestration frameworks, transformation pipelines, streaming services, and analytical consumption layers.
• Experience designing and implementing monitoring, observability, logging, alerting, and incident management approaches for Databricks workloads and Azure data services, using tools such as Azure Monitor, Log Analytics, or similar.
• Strong understanding of data quality, reconciliation, validation, and lineage concepts, and practical experience implementing control frameworks that protect critical data flows and products.
• Hands-on experience with Azure Purview or comparable data cataloge and lineage tooling, including configuration of collections, classification, ownership, and lineage for key datasets.
• Good understanding of reliability engineering principles such as availability targets, resilience patterns, recoverability, service health indicators, and operational readiness assessments.
• Experience using scripting and automation (for example, Python, PowerShell, or similar) to remove operational toil, improve repeatability, and strengthen recovery and deployment processes.
• Ability to diagnose and resolve complex issues that span data pipelines, integrations, cloud infrastructure, configuration, and source or downstream systems, and to drive pragmatic remediation.
• Strong collaboration and communication skills, with the ability to work effectively across data engineering, architecture, cloud platform, security, delivery, and operational teams, and to explain issues and trade-offs clearly to technical and non-technical stakeholders.
• Experience with Azure-native observability tooling and patterns for Databricks and the wider Azure data stack, and exposure to equivalent AWS monitoring approaches.
Desirable Skills - What Makes You Stand Out
• Experience tuning and optimising Databricks jobs, clusters, and workflows for performance, cost efficiency, and reliability in production environments.
• Familiarity with CI/CD practices, infrastructure as code, and automated testing for data platforms, supporting safe, repeatable, and low-risk changes to data services.
• Experience working in regulated or contractually governed environments such as public sector, health, employment services, or similarly controlled industries, where se...
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Type: Permanent Location: Jackson, US-MS
Salary / Rate: Not Specified
Posted: 2026-06-04 08:36:01
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Key Responsibilities
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Essential Skills - What You'll Bring
• Proven experience in data engineering, platform engineering, site reliability engineering, DataOps, or a closely related role focused on data platform reliability and operations.
• Strong hands-on experience with Azure-based data platforms, particularly Azure Databricks and core Azure data services such as Data Lake Storage, Data Factory/Synapse, and analytical stores, with familiarity of equivalent services in AWS.
• Strong understanding of modern data platform architectures, including data lakes, warehouses or lakehouses, orchestration frameworks, transformation pipelines, streaming services, and analytical consumption layers.
• Experience designing and implementing monitoring, observability, logging, alerting, and incident management approaches for Databricks workloads and Azure data services, using tools such as Azure Monitor, Log Analytics, or similar.
• Strong understanding of data quality, reconciliation, validation, and lineage concepts, and practical experience implementing control frameworks that protect critical data flows and products.
• Hands-on experience with Azure Purview or comparable data cataloge and lineage tooling, including configuration of collections, classification, ownership, and lineage for key datasets.
• Good understanding of reliability engineering principles such as availability targets, resilience patterns, recoverability, service health indicators, and operational readiness assessments.
• Experience using scripting and automation (for example, Python, PowerShell, or similar) to remove operational toil, improve repeatability, and strengthen recovery and deployment processes.
• Ability to diagnose and resolve complex issues that span data pipelines, integrations, cloud infrastructure, configuration, and source or downstream systems, and to drive pragmatic remediation.
• Strong collaboration and communication skills, with the ability to work effectively across data engineering, architecture, cloud platform, security, delivery, and operational teams, and to explain issues and trade-offs clearly to technical and non-technical stakeholders.
• Experience with Azure-native observability tooling and patterns for Databricks and the wider Azure data stack, and exposure to equivalent AWS monitoring approaches.
Desirable Skills - What Makes You Stand Out
• Experience tuning and optimising Databricks jobs, clusters, and workflows for performance, cost efficiency, and reliability in production environments.
• Familiarity with CI/CD practices, infrastructure as code, and automated testing for data platforms, supporting safe, repeatable, and low-risk changes to data services.
• Experience working in regulated or contractually governed environments such as public sector, health, employment services, or similarly controlled industries, where se...
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Type: Permanent Location: Detroit, US-MI
Salary / Rate: Not Specified
Posted: 2026-06-04 08:36:01
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Key Responsibilities
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Essential Skills - What You'll Bring
• Proven experience in data engineering, platform engineering, site reliability engineering, DataOps, or a closely related role focused on data platform reliability and operations.
• Strong hands-on experience with Azure-based data platforms, particularly Azure Databricks and core Azure data services such as Data Lake Storage, Data Factory/Synapse, and analytical stores, with familiarity of equivalent services in AWS.
• Strong understanding of modern data platform architectures, including data lakes, warehouses or lakehouses, orchestration frameworks, transformation pipelines, streaming services, and analytical consumption layers.
• Experience designing and implementing monitoring, observability, logging, alerting, and incident management approaches for Databricks workloads and Azure data services, using tools such as Azure Monitor, Log Analytics, or similar.
• Strong understanding of data quality, reconciliation, validation, and lineage concepts, and practical experience implementing control frameworks that protect critical data flows and products.
• Hands-on experience with Azure Purview or comparable data cataloge and lineage tooling, including configuration of collections, classification, ownership, and lineage for key datasets.
• Good understanding of reliability engineering principles such as availability targets, resilience patterns, recoverability, service health indicators, and operational readiness assessments.
• Experience using scripting and automation (for example, Python, PowerShell, or similar) to remove operational toil, improve repeatability, and strengthen recovery and deployment processes.
• Ability to diagnose and resolve complex issues that span data pipelines, integrations, cloud infrastructure, configuration, and source or downstream systems, and to drive pragmatic remediation.
• Strong collaboration and communication skills, with the ability to work effectively across data engineering, architecture, cloud platform, security, delivery, and operational teams, and to explain issues and trade-offs clearly to technical and non-technical stakeholders.
• Experience with Azure-native observability tooling and patterns for Databricks and the wider Azure data stack, and exposure to equivalent AWS monitoring approaches.
Desirable Skills - What Makes You Stand Out
• Experience tuning and optimising Databricks jobs, clusters, and workflows for performance, cost efficiency, and reliability in production environments.
• Familiarity with CI/CD practices, infrastructure as code, and automated testing for data platforms, supporting safe, repeatable, and low-risk changes to data services.
• Experience working in regulated or contractually governed environments such as public sector, health, employment services, or similarly controlled industries, where se...
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Type: Permanent Location: Boston, US-MA
Salary / Rate: Not Specified
Posted: 2026-06-04 08:36:00
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Key Responsibilities
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*
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*
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*
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Essential Skills - What You'll Bring
• Proven experience in data engineering, platform engineering, site reliability engineering, DataOps, or a closely related role focused on data platform reliability and operations.
• Strong hands-on experience with Azure-based data platforms, particularly Azure Databricks and core Azure data services such as Data Lake Storage, Data Factory/Synapse, and analytical stores, with familiarity of equivalent services in AWS.
• Strong understanding of modern data platform architectures, including data lakes, warehouses or lakehouses, orchestration frameworks, transformation pipelines, streaming services, and analytical consumption layers.
• Experience designing and implementing monitoring, observability, logging, alerting, and incident management approaches for Databricks workloads and Azure data services, using tools such as Azure Monitor, Log Analytics, or similar.
• Strong understanding of data quality, reconciliation, validation, and lineage concepts, and practical experience implementing control frameworks that protect critical data flows and products.
• Hands-on experience with Azure Purview or comparable data cataloge and lineage tooling, including configuration of collections, classification, ownership, and lineage for key datasets.
• Good understanding of reliability engineering principles such as availability targets, resilience patterns, recoverability, service health indicators, and operational readiness assessments.
• Experience using scripting and automation (for example, Python, PowerShell, or similar) to remove operational toil, improve repeatability, and strengthen recovery and deployment processes.
• Ability to diagnose and resolve complex issues that span data pipelines, integrations, cloud infrastructure, configuration, and source or downstream systems, and to drive pragmatic remediation.
• Strong collaboration and communication skills, with the ability to work effectively across data engineering, architecture, cloud platform, security, delivery, and operational teams, and to explain issues and trade-offs clearly to technical and non-technical stakeholders.
• Experience with Azure-native observability tooling and patterns for Databricks and the wider Azure data stack, and exposure to equivalent AWS monitoring approaches.
Desirable Skills - What Makes You Stand Out
• Experience tuning and optimising Databricks jobs, clusters, and workflows for performance, cost efficiency, and reliability in production environments.
• Familiarity with CI/CD practices, infrastructure as code, and automated testing for data platforms, supporting safe, repeatable, and low-risk changes to data services.
• Experience working in regulated or contractually governed environments such as public sector, health, employment services, or similarly controlled industries, where se...
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Type: Permanent Location: Aberdeen, US-MD
Salary / Rate: Not Specified
Posted: 2026-06-04 08:36:00
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Key Responsibilities
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Essential Skills - What You'll Bring
• Proven experience in data engineering, platform engineering, site reliability engineering, DataOps, or a closely related role focused on data platform reliability and operations.
• Strong hands-on experience with Azure-based data platforms, particularly Azure Databricks and core Azure data services such as Data Lake Storage, Data Factory/Synapse, and analytical stores, with familiarity of equivalent services in AWS.
• Strong understanding of modern data platform architectures, including data lakes, warehouses or lakehouses, orchestration frameworks, transformation pipelines, streaming services, and analytical consumption layers.
• Experience designing and implementing monitoring, observability, logging, alerting, and incident management approaches for Databricks workloads and Azure data services, using tools such as Azure Monitor, Log Analytics, or similar.
• Strong understanding of data quality, reconciliation, validation, and lineage concepts, and practical experience implementing control frameworks that protect critical data flows and products.
• Hands-on experience with Azure Purview or comparable data cataloge and lineage tooling, including configuration of collections, classification, ownership, and lineage for key datasets.
• Good understanding of reliability engineering principles such as availability targets, resilience patterns, recoverability, service health indicators, and operational readiness assessments.
• Experience using scripting and automation (for example, Python, PowerShell, or similar) to remove operational toil, improve repeatability, and strengthen recovery and deployment processes.
• Ability to diagnose and resolve complex issues that span data pipelines, integrations, cloud infrastructure, configuration, and source or downstream systems, and to drive pragmatic remediation.
• Strong collaboration and communication skills, with the ability to work effectively across data engineering, architecture, cloud platform, security, delivery, and operational teams, and to explain issues and trade-offs clearly to technical and non-technical stakeholders.
• Experience with Azure-native observability tooling and patterns for Databricks and the wider Azure data stack, and exposure to equivalent AWS monitoring approaches.
Desirable Skills - What Makes You Stand Out
• Experience tuning and optimising Databricks jobs, clusters, and workflows for performance, cost efficiency, and reliability in production environments.
• Familiarity with CI/CD practices, infrastructure as code, and automated testing for data platforms, supporting safe, repeatable, and low-risk changes to data services.
• Experience working in regulated or contractually governed environments such as public sector, health, employment services, or similarly controlled industries, where se...
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Type: Permanent Location: Springfield, US-MA
Salary / Rate: Not Specified
Posted: 2026-06-04 08:35:59
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Key Responsibilities
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Essential Skills - What You'll Bring
• Proven experience in data engineering, platform engineering, site reliability engineering, DataOps, or a closely related role focused on data platform reliability and operations.
• Strong hands-on experience with Azure-based data platforms, particularly Azure Databricks and core Azure data services such as Data Lake Storage, Data Factory/Synapse, and analytical stores, with familiarity of equivalent services in AWS.
• Strong understanding of modern data platform architectures, including data lakes, warehouses or lakehouses, orchestration frameworks, transformation pipelines, streaming services, and analytical consumption layers.
• Experience designing and implementing monitoring, observability, logging, alerting, and incident management approaches for Databricks workloads and Azure data services, using tools such as Azure Monitor, Log Analytics, or similar.
• Strong understanding of data quality, reconciliation, validation, and lineage concepts, and practical experience implementing control frameworks that protect critical data flows and products.
• Hands-on experience with Azure Purview or comparable data cataloge and lineage tooling, including configuration of collections, classification, ownership, and lineage for key datasets.
• Good understanding of reliability engineering principles such as availability targets, resilience patterns, recoverability, service health indicators, and operational readiness assessments.
• Experience using scripting and automation (for example, Python, PowerShell, or similar) to remove operational toil, improve repeatability, and strengthen recovery and deployment processes.
• Ability to diagnose and resolve complex issues that span data pipelines, integrations, cloud infrastructure, configuration, and source or downstream systems, and to drive pragmatic remediation.
• Strong collaboration and communication skills, with the ability to work effectively across data engineering, architecture, cloud platform, security, delivery, and operational teams, and to explain issues and trade-offs clearly to technical and non-technical stakeholders.
• Experience with Azure-native observability tooling and patterns for Databricks and the wider Azure data stack, and exposure to equivalent AWS monitoring approaches.
Desirable Skills - What Makes You Stand Out
• Experience tuning and optimising Databricks jobs, clusters, and workflows for performance, cost efficiency, and reliability in production environments.
• Familiarity with CI/CD practices, infrastructure as code, and automated testing for data platforms, supporting safe, repeatable, and low-risk changes to data services.
• Experience working in regulated or contractually governed environments such as public sector, health, employment services, or similarly controlled industries, where se...
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Type: Permanent Location: Bangor, US-ME
Salary / Rate: Not Specified
Posted: 2026-06-04 08:35:58
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Key Responsibilities
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Essential Skills - What You'll Bring
• Proven experience in data engineering, platform engineering, site reliability engineering, DataOps, or a closely related role focused on data platform reliability and operations.
• Strong hands-on experience with Azure-based data platforms, particularly Azure Databricks and core Azure data services such as Data Lake Storage, Data Factory/Synapse, and analytical stores, with familiarity of equivalent services in AWS.
• Strong understanding of modern data platform architectures, including data lakes, warehouses or lakehouses, orchestration frameworks, transformation pipelines, streaming services, and analytical consumption layers.
• Experience designing and implementing monitoring, observability, logging, alerting, and incident management approaches for Databricks workloads and Azure data services, using tools such as Azure Monitor, Log Analytics, or similar.
• Strong understanding of data quality, reconciliation, validation, and lineage concepts, and practical experience implementing control frameworks that protect critical data flows and products.
• Hands-on experience with Azure Purview or comparable data cataloge and lineage tooling, including configuration of collections, classification, ownership, and lineage for key datasets.
• Good understanding of reliability engineering principles such as availability targets, resilience patterns, recoverability, service health indicators, and operational readiness assessments.
• Experience using scripting and automation (for example, Python, PowerShell, or similar) to remove operational toil, improve repeatability, and strengthen recovery and deployment processes.
• Ability to diagnose and resolve complex issues that span data pipelines, integrations, cloud infrastructure, configuration, and source or downstream systems, and to drive pragmatic remediation.
• Strong collaboration and communication skills, with the ability to work effectively across data engineering, architecture, cloud platform, security, delivery, and operational teams, and to explain issues and trade-offs clearly to technical and non-technical stakeholders.
• Experience with Azure-native observability tooling and patterns for Databricks and the wider Azure data stack, and exposure to equivalent AWS monitoring approaches.
Desirable Skills - What Makes You Stand Out
• Experience tuning and optimising Databricks jobs, clusters, and workflows for performance, cost efficiency, and reliability in production environments.
• Familiarity with CI/CD practices, infrastructure as code, and automated testing for data platforms, supporting safe, repeatable, and low-risk changes to data services.
• Experience working in regulated or contractually governed environments such as public sector, health, employment services, or similarly controlled industries, where se...
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Type: Permanent Location: Baltimore, US-MD
Salary / Rate: Not Specified
Posted: 2026-06-04 08:35:58
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Create an outstanding customer experience and inspire associates to deliver excellent customer service.
Establish and maintain a safe, clean environment that encourages our customers to return.
Achieve sales and profit goals established for the department, control all established quality assurance standards and expenses and properly schedule and staff technicians to meet the needs of the business.
Monitor all functions, duties and activities for the department.
Demonstrate the company's core values of respect, honesty, integrity, diversity, inclusion and safety.Based in Portland, Oregon, Fred Meyer merged with The Kroger Company in 1998.
Today, we're proudly serving Fred Meyer customers in over 120 stores throughout Oregon, Washington, Idaho and Alaska.
As part of the Kroger family of companies, we take pride in bringing diverse teams with a passion for food and people together with one common purpose: To Feed the Human Spirit.
With a history of innovation, we work tirelessly to create amazing experiences for our customers, communities AND each other, with food at the heart of it all.
Here, people matter.
That's why we strive to provide the ingredients you need to create your own recipe for success at work and in life.
We help feed your future by providing the value and care you need to grow.
If you're caring, purpose-driven and hungry to learn, your potential is unlimited.
Whether you're seeking a part-time position or a new career path, we've got a fresh opportunity for you.
Apply today to become part of our Fred Meyer family!
What you'll receive from us:
The Kroger Family of Companies offers comprehensive benefits to support your Associate Well-Being, including Physical, Emotional, Financial and more.
We'll help you thrive, with access to:
* A wide range of healthcare coverage, including affordable, comprehensive medical, dental, vision and prescription coverage, through company plans or collective bargaining agreement plans.
* Flexible scheduling in full- and part-time roles with paid time off, including holiday and sick pay based on eligibility and length of service.
* Emotional and financial support with free counseling through our Employee Assistance Program and free, confidential financial tools and coaching with Goldman Sachs Ayco.
* Valuable associate discounts on purchases, including food, travel, technology and so much more.
* Up to $21,000 in tuition reimbursement over your career, through our industry-leading Continuing Education program.
* Vast potential for growth, through an abundance of industry-leading training programs and diverse career pathways.
For more information about benefits and eligibility, please visit our Benefits Page ! Minimum
- Bachelor's Degree Pharmacy
- Current state pharmacist licensure in good standing
- Ability to handle stressful situations
- Knowledge of basic math (counting, addition, and subtraction)
- Effective oral/written communication skills
Desired
- 1 year o...
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Type: Permanent Location: Newport, US-OR
Salary / Rate: Not Specified
Posted: 2026-06-04 08:35:57
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Key Responsibilities
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Essential Skills - What You'll Bring
• Proven experience in data engineering, platform engineering, site reliability engineering, DataOps, or a closely related role focused on data platform reliability and operations.
• Strong hands-on experience with Azure-based data platforms, particularly Azure Databricks and core Azure data services such as Data Lake Storage, Data Factory/Synapse, and analytical stores, with familiarity of equivalent services in AWS.
• Strong understanding of modern data platform architectures, including data lakes, warehouses or lakehouses, orchestration frameworks, transformation pipelines, streaming services, and analytical consumption layers.
• Experience designing and implementing monitoring, observability, logging, alerting, and incident management approaches for Databricks workloads and Azure data services, using tools such as Azure Monitor, Log Analytics, or similar.
• Strong understanding of data quality, reconciliation, validation, and lineage concepts, and practical experience implementing control frameworks that protect critical data flows and products.
• Hands-on experience with Azure Purview or comparable data cataloge and lineage tooling, including configuration of collections, classification, ownership, and lineage for key datasets.
• Good understanding of reliability engineering principles such as availability targets, resilience patterns, recoverability, service health indicators, and operational readiness assessments.
• Experience using scripting and automation (for example, Python, PowerShell, or similar) to remove operational toil, improve repeatability, and strengthen recovery and deployment processes.
• Ability to diagnose and resolve complex issues that span data pipelines, integrations, cloud infrastructure, configuration, and source or downstream systems, and to drive pragmatic remediation.
• Strong collaboration and communication skills, with the ability to work effectively across data engineering, architecture, cloud platform, security, delivery, and operational teams, and to explain issues and trade-offs clearly to technical and non-technical stakeholders.
• Experience with Azure-native observability tooling and patterns for Databricks and the wider Azure data stack, and exposure to equivalent AWS monitoring approaches.
Desirable Skills - What Makes You Stand Out
• Experience tuning and optimising Databricks jobs, clusters, and workflows for performance, cost efficiency, and reliability in production environments.
• Familiarity with CI/CD practices, infrastructure as code, and automated testing for data platforms, supporting safe, repeatable, and low-risk changes to data services.
• Experience working in regulated or contractually governed environments such as public sector, health, employment services, or similarly controlled industries, where se...
....Read more...
Type: Permanent Location: New Orleans, US-LA
Salary / Rate: Not Specified
Posted: 2026-06-04 08:35:56
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Key Responsibilities
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Essential Skills - What You'll Bring
• Proven experience in data engineering, platform engineering, site reliability engineering, DataOps, or a closely related role focused on data platform reliability and operations.
• Strong hands-on experience with Azure-based data platforms, particularly Azure Databricks and core Azure data services such as Data Lake Storage, Data Factory/Synapse, and analytical stores, with familiarity of equivalent services in AWS.
• Strong understanding of modern data platform architectures, including data lakes, warehouses or lakehouses, orchestration frameworks, transformation pipelines, streaming services, and analytical consumption layers.
• Experience designing and implementing monitoring, observability, logging, alerting, and incident management approaches for Databricks workloads and Azure data services, using tools such as Azure Monitor, Log Analytics, or similar.
• Strong understanding of data quality, reconciliation, validation, and lineage concepts, and practical experience implementing control frameworks that protect critical data flows and products.
• Hands-on experience with Azure Purview or comparable data cataloge and lineage tooling, including configuration of collections, classification, ownership, and lineage for key datasets.
• Good understanding of reliability engineering principles such as availability targets, resilience patterns, recoverability, service health indicators, and operational readiness assessments.
• Experience using scripting and automation (for example, Python, PowerShell, or similar) to remove operational toil, improve repeatability, and strengthen recovery and deployment processes.
• Ability to diagnose and resolve complex issues that span data pipelines, integrations, cloud infrastructure, configuration, and source or downstream systems, and to drive pragmatic remediation.
• Strong collaboration and communication skills, with the ability to work effectively across data engineering, architecture, cloud platform, security, delivery, and operational teams, and to explain issues and trade-offs clearly to technical and non-technical stakeholders.
• Experience with Azure-native observability tooling and patterns for Databricks and the wider Azure data stack, and exposure to equivalent AWS monitoring approaches.
Desirable Skills - What Makes You Stand Out
• Experience tuning and optimising Databricks jobs, clusters, and workflows for performance, cost efficiency, and reliability in production environments.
• Familiarity with CI/CD practices, infrastructure as code, and automated testing for data platforms, supporting safe, repeatable, and low-risk changes to data services.
• Experience working in regulated or contractually governed environments such as public sector, health, employment services, or similarly controlled industries, where se...
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Type: Permanent Location: Bowling Green, US-KY
Salary / Rate: Not Specified
Posted: 2026-06-04 08:35:56
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Key Responsibilities
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Essential Skills - What You'll Bring
• Proven experience in data engineering, platform engineering, site reliability engineering, DataOps, or a closely related role focused on data platform reliability and operations.
• Strong hands-on experience with Azure-based data platforms, particularly Azure Databricks and core Azure data services such as Data Lake Storage, Data Factory/Synapse, and analytical stores, with familiarity of equivalent services in AWS.
• Strong understanding of modern data platform architectures, including data lakes, warehouses or lakehouses, orchestration frameworks, transformation pipelines, streaming services, and analytical consumption layers.
• Experience designing and implementing monitoring, observability, logging, alerting, and incident management approaches for Databricks workloads and Azure data services, using tools such as Azure Monitor, Log Analytics, or similar.
• Strong understanding of data quality, reconciliation, validation, and lineage concepts, and practical experience implementing control frameworks that protect critical data flows and products.
• Hands-on experience with Azure Purview or comparable data cataloge and lineage tooling, including configuration of collections, classification, ownership, and lineage for key datasets.
• Good understanding of reliability engineering principles such as availability targets, resilience patterns, recoverability, service health indicators, and operational readiness assessments.
• Experience using scripting and automation (for example, Python, PowerShell, or similar) to remove operational toil, improve repeatability, and strengthen recovery and deployment processes.
• Ability to diagnose and resolve complex issues that span data pipelines, integrations, cloud infrastructure, configuration, and source or downstream systems, and to drive pragmatic remediation.
• Strong collaboration and communication skills, with the ability to work effectively across data engineering, architecture, cloud platform, security, delivery, and operational teams, and to explain issues and trade-offs clearly to technical and non-technical stakeholders.
• Experience with Azure-native observability tooling and patterns for Databricks and the wider Azure data stack, and exposure to equivalent AWS monitoring approaches.
Desirable Skills - What Makes You Stand Out
• Experience tuning and optimising Databricks jobs, clusters, and workflows for performance, cost efficiency, and reliability in production environments.
• Familiarity with CI/CD practices, infrastructure as code, and automated testing for data platforms, supporting safe, repeatable, and low-risk changes to data services.
• Experience working in regulated or contractually governed environments such as public sector, health, employment services, or similarly controlled industries, where se...
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Type: Permanent Location: Shreveport, US-LA
Salary / Rate: Not Specified
Posted: 2026-06-04 08:35:55
