Azure Data Engineer
Requirements
• Azure Data Factory (ADF), Azure Synapse Analytics, Azure SQL, ADLS, and Microsoft Fabric.
• Strong experience with ETL/ELT processes and data integration.
• Advanced SQL/T-SQL development and database optimization.
• Enterprise Data Warehouse (EDW) concepts and implementation.
• Data modelling including fact/dimension structures and source-to-target mapping.
• Azure DevOps, Git, CI/CD, and release management.
• Pipeline orchestration, monitoring, troubleshooting, and production support.
• Power BI data models and reporting knowledge.
• Strong communication, analytical, and documentation skills.
Preferred Qualifications
• Bachelor’s degree in Computer Science, Information Technology, Engineering, or related field.
• Microsoft Azure certifications such as DP-203 or Microsoft Fabric certifications
Key Responsibilities
• Design, develop, and maintain scalable data pipelines using Azure Data Factory (ADF), Azure Synapse Analytics, Microsoft Fabric, Azure SQL Database, and Azure Data Lake Storage (ADLS).
• Build and orchestrate ADF pipelines to ingest data from multiple enterprise systems into the Enterprise Data Warehouse (EDW).
• Develop and optimize ETL/ELT processes for reliable data movement and transformation.
• Create complex SQL/T-SQL queries, stored procedures, views, and data transformation logic.
• Integrate data from diverse sources including databases, APIs, cloud applications, and files.
• Monitor, troubleshoot, and optimize pipelines and production workloads.
• Participate in requirements gathering, design, development, testing, deployment, and support activities.
• Implement CI/CD processes using Azure DevOps and Git.
• Utilize Azure Key Vault, Logic Apps, Azure Functions, and Storage services.
• Support Power BI reporting and analytics requirements.
[overview]We are seeking a skilled and motivated Azure Data Engineer with expertise in Azure Data Platform technologies, Enterprise Data Warehousing (EDW), ETL/ELT development, and Microsoft Fabric. The candidate will design, develop, and support scalable data integration solutions and data warehouses.
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