Data Engineer

• Pipeline Engineering: Design, build, and maintain scalable ETL/ELT pipelines using Microsoft Fabric (Dataflows Gen2, Pipelines, Notebooks, Spark) alongside legacy SSIS workflows.
• Medallion Architecture: Implement Bronze, Silver, and Gold layers utilizing Delta Lake, Warehouse, and OneLake structures.
• Data Modeling & Optimization: Build high-performance star schemas, handle SCD Type 1/2, and implement partitioning, Z-ordering, and compaction.
• Data Ingestion: Develop ingestion frameworks for REST APIs, SaaS platforms, flat files, cloud feeds, and partner integrations.
• Governance & Security: Implement Row-Level Security (RLS), object-level controls, and data governance/lineage via Microsoft Purview.
• Operational Excellence: Maintain CI/CD pipelines via Azure DevOps/Git and troubleshoot pipeline bottlenecks.

Required Qualifications

• Bachelor's degree in CS, Information Systems, Engineering, or a related field.
• 5+ years of core Data Engineering, BI, or Data Warehouse development experience.
• Strong hands-on expertise with Microsoft Fabric (Lakehouse, OneLake, Pipelines, Notebooks).
• Advanced SQL (T-SQL) capabilities for complex transformations, joins, and query optimization.
• High proficiency in Python or PySpark for data transformations and ingestion.
• Solid grasp of Kimball dimensional modeling, star schemas, and conformed dimensions.
• 3-5 years of hands-on experience with SSIS / SSMS / SSDT.
• Proven track record with CI/CD deployment via Azure DevOps / Git.

Nice-to-Have

• Domain experience in Retail / QSR (Quick Service Restaurant) data environments (POS, supply chain, labor, or inventory).
• Exposure to Power BI semantic modeling, Azure Data Factory, Synapse, or Databricks.