What are the responsibilities and job description for the Immediate Hire_Data Engineer (Azure Databricks, Azure Data Lake) position at Jobs via Dice?
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Role Summary
Data Engineer – Job Description
We are looking for a Data Engineer to design, build, support, and improve cloud-based data platform (Azure) and enterprise data solutions. This role focuses on developing and maintaining scalable data pipelines, supporting platform operations and deployment activities, troubleshooting data and infrastructure issues, and partnering with engineering and business teams to deliver reliable data services. The ideal candidate should be comfortable working across modern Azure data and platform services, including data integration, analytics, operational support, and engineering workflows.
Key Responsibilities
Design, develop, and maintain data pipelines and ETL/ELT workflows for cloud-based data platforms and enterprise reporting solutions.
Build and support solutions using Azure platform services and related data technologies, including Azure Synapse Analytics, Azure Data Factory (ADF), Azure Databricks, ADLS, and Event Hubs.
Support deployment, release validation, and environment testing activities across development, integration, and production environments.
Investigate and resolve data pipeline failures, data quality issues, and platform-related incidents impacting downstream consumers and operational reporting.
Work with Azure DevOps and related engineering processes to support deliverable tracking, release coordination, work item management, and pipeline/repository-based engineering workflows.
Participate in operational support activities, service engineering responsibilities, and readiness for on-call or incident-response processes when needed.
Required Qualifications
Hands-on experience building and supporting data pipelines and large-scale data processing solutions.
Strong experience with SQL, Python, and Spark for data transformation, processing, and analysis.
Experience with Azure cloud data services and platform components, especially Azure Synapse Analytics, Azure Data Factory, Azure Databricks, ADLS, and Event Hubs.
Experience using Azure DevOps or similar engineering tools for work item tracking, release coordination, or deployment support.
Ability to troubleshoot production issues, support deployment validation, and maintain operational stability of enterprise data systems.
Role Summary
Data Engineer – Job Description
We are looking for a Data Engineer to design, build, support, and improve cloud-based data platform (Azure) and enterprise data solutions. This role focuses on developing and maintaining scalable data pipelines, supporting platform operations and deployment activities, troubleshooting data and infrastructure issues, and partnering with engineering and business teams to deliver reliable data services. The ideal candidate should be comfortable working across modern Azure data and platform services, including data integration, analytics, operational support, and engineering workflows.
Key Responsibilities
Design, develop, and maintain data pipelines and ETL/ELT workflows for cloud-based data platforms and enterprise reporting solutions.
Build and support solutions using Azure platform services and related data technologies, including Azure Synapse Analytics, Azure Data Factory (ADF), Azure Databricks, ADLS, and Event Hubs.
Support deployment, release validation, and environment testing activities across development, integration, and production environments.
Investigate and resolve data pipeline failures, data quality issues, and platform-related incidents impacting downstream consumers and operational reporting.
Work with Azure DevOps and related engineering processes to support deliverable tracking, release coordination, work item management, and pipeline/repository-based engineering workflows.
Participate in operational support activities, service engineering responsibilities, and readiness for on-call or incident-response processes when needed.
Required Qualifications
Hands-on experience building and supporting data pipelines and large-scale data processing solutions.
Strong experience with SQL, Python, and Spark for data transformation, processing, and analysis.
Experience with Azure cloud data services and platform components, especially Azure Synapse Analytics, Azure Data Factory, Azure Databricks, ADLS, and Event Hubs.
Experience using Azure DevOps or similar engineering tools for work item tracking, release coordination, or deployment support.
Ability to troubleshoot production issues, support deployment validation, and maintain operational stability of enterprise data systems.