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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: Manchester, US-NH
Salary / Rate: Not Specified
Posted: 2026-06-04 08:36:16
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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: Cherry Hill, US-NJ
Salary / Rate: Not Specified
Posted: 2026-06-04 08:36:15
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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: Albuquerque, US-NM
Salary / Rate: Not Specified
Posted: 2026-06-04 08:36:15
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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 Cruces, US-NM
Salary / Rate: Not Specified
Posted: 2026-06-04 08:36:14
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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: Lebanon, US-NH
Salary / Rate: Not Specified
Posted: 2026-06-04 08:36:14
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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: Bozeman, US-MT
Salary / Rate: Not Specified
Posted: 2026-06-04 08:36:13
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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: North Platte, US-NE
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: 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: 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: 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: 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...
....Read more...
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...
....Read more...
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...
....Read more...
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...
....Read more...
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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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: Aberdeen, US-MD
Salary / Rate: Not Specified
Posted: 2026-06-04 08:36:00
