Data Warehouse Engineer

Roles & Responsibilities

• Design and implement scalable cloud-based data warehouse solutions using Azure Synapse Analytics
• Define and maintain enterprise data warehouse architecture as a single source of truth
• Develop and optimize dimensional data models (fact/dimension tables) for BI reporting
• Build and maintain ETL/ELT pipelines using Azure Data Factory and Azure Databricks
• Ingest, transform, and load data from multiple structured and unstructured sources into Azure Data Lake and Synapse
• Optimize SQL queries and manage database performance through indexing, partitioning, and compute tuning
• Ensure high availability and scalability of data warehouse solutions
• Integrate relational and non-relational data within Azure ecosystem
• Analyze and modernize legacy mainframe systems including COBOL, JCL, CICS/IMS, DB2, and VSAM
• Implement CI/CD pipelines using Git, Jenkins, GitHub, or Azure DevOps
• Ensure version control, automated deployments, and release management
• Collaborate with business and technical stakeholders to translate requirements into scalable data solutions
• Provide technical leadership and problem-solving support across data initiatives

Required Skills

• Strong experience with SSRS, Databricks, Azure Data Lake Storage Gen2, Azure Analysis Services
• Hands-on experience with Azure Synapse Analytics (SQL Data Warehouse)
• Expertise in Azure Data Factory (ADF) and/or Azure Databricks for ETL/ELT pipelines
• Strong knowledge of SQL performance tuning, indexing, partitioning, and query optimization
• Experience implementing CI/CD pipelines using Git, Jenkins, GitHub, or Azure DevOps
• Strong understanding of dimensional data modeling (fact & dimension tables) and Medallion architecture (Gold layer)
• Experience integrating structured and unstructured data using Azure Data Lake
• Strong analytical, communication, and stakeholder management skills
• Experience analyzing mainframe legacy systems (COBOL, JCL, CICS/IMS, DB2, VSAM)

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