-
Key Responsibilities
*
*
*
*
*
*
*
*
*
*
*
*
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: Spokane, US-WA
Salary / Rate: Not Specified
Posted: 2026-06-04 08:37:09
-
Key Responsibilities
*
*
*
*
*
*
*
*
*
*
*
*
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: Milwaukee, US-WI
Salary / Rate: Not Specified
Posted: 2026-06-04 08:37:08
-
Key Responsibilities
*
*
*
*
*
*
*
*
*
*
*
*
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: Charleston, US-WV
Salary / Rate: Not Specified
Posted: 2026-06-04 08:37:06
-
Key Responsibilities
*
*
*
*
*
*
*
*
*
*
*
*
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: Seattle, US-WA
Salary / Rate: Not Specified
Posted: 2026-06-04 08:37:03
-
Key Responsibilities
*
*
*
*
*
*
*
*
*
*
*
*
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: Eau Claire, US-WI
Salary / Rate: Not Specified
Posted: 2026-06-04 08:37:03
-
Key Responsibilities
*
*
*
*
*
*
*
*
*
*
*
*
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: Bennington, US-VT
Salary / Rate: Not Specified
Posted: 2026-06-04 08:37:02
-
Key Responsibilities
*
*
*
*
*
*
*
*
*
*
*
*
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: Morgantown, US-WV
Salary / Rate: Not Specified
Posted: 2026-06-04 08:37:02
-
Key Responsibilities
*
*
*
*
*
*
*
*
*
*
*
*
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: Tysons, US-VA
Salary / Rate: Not Specified
Posted: 2026-06-04 08:36:59
-
Key Responsibilities
*
*
*
*
*
*
*
*
*
*
*
*
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: Richmond, US-VA
Salary / Rate: Not Specified
Posted: 2026-06-04 08:36:57
-
Key Responsibilities
*
*
*
*
*
*
*
*
*
*
*
*
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: Roanoke, US-VA
Salary / Rate: Not Specified
Posted: 2026-06-04 08:36:54
-
Key Responsibilities
*
*
*
*
*
*
*
*
*
*
*
*
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: Burlington, US-VT
Salary / Rate: Not Specified
Posted: 2026-06-04 08:36:51
-
Key Responsibilities
*
*
*
*
*
*
*
*
*
*
*
*
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: Salt Lake City, US-UT
Salary / Rate: Not Specified
Posted: 2026-06-04 08:36:49
-
Key Responsibilities
*
*
*
*
*
*
*
*
*
*
*
*
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. George, US-UT
Salary / Rate: Not Specified
Posted: 2026-06-04 08:36:48
-
Key Responsibilities
*
*
*
*
*
*
*
*
*
*
*
*
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: San Antonio, US-TX
Salary / Rate: Not Specified
Posted: 2026-06-04 08:36:48
-
Key Responsibilities
*
*
*
*
*
*
*
*
*
*
*
*
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: Dallas, US-TX
Salary / Rate: Not Specified
Posted: 2026-06-04 08:36:47
-
Key Responsibilities
*
*
*
*
*
*
*
*
*
*
*
*
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: Houston, US-TX
Salary / Rate: Not Specified
Posted: 2026-06-04 08:36:45
-
Key Responsibilities
*
*
*
*
*
*
*
*
*
*
*
*
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: Lubbock, US-TX
Salary / Rate: Not Specified
Posted: 2026-06-04 08:36:42
-
Key Responsibilities
*
*
*
*
*
*
*
*
*
*
*
*
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: Rapid City, US-SD
Salary / Rate: Not Specified
Posted: 2026-06-04 08:36:40
-
Key Responsibilities
*
*
*
*
*
*
*
*
*
*
*
*
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: Charleston, US-SC
Salary / Rate: Not Specified
Posted: 2026-06-04 08:36:38
-
Key Responsibilities
*
*
*
*
*
*
*
*
*
*
*
*
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: Memphis, US-TN
Salary / Rate: Not Specified
Posted: 2026-06-04 08:36:36
-
Key Responsibilities
*
*
*
*
*
*
*
*
*
*
*
*
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: Columbia, US-SC
Salary / Rate: Not Specified
Posted: 2026-06-04 08:36:33
-
Key Responsibilities
*
*
*
*
*
*
*
*
*
*
*
*
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: Nashville, US-TN
Salary / Rate: Not Specified
Posted: 2026-06-04 08:36:31
-
Key Responsibilities
*
*
*
*
*
*
*
*
*
*
*
*
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: Eugene, US-OR
Salary / Rate: Not Specified
Posted: 2026-06-04 08:36:29
-
Key Responsibilities
*
*
*
*
*
*
*
*
*
*
*
*
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: Sioux Falls, US-SD
Salary / Rate: Not Specified
Posted: 2026-06-04 08:36:29
-
Key Responsibilities
*
*
*
*
*
*
*
*
*
*
*
*
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: Pittsburgh, US-PA
Salary / Rate: Not Specified
Posted: 2026-06-04 08:36:28
