Microsoft Fabric Data Engineer

Responsibilities

• Implement end-to-end Microsoft Fabric solutions based on approved architecture, including OneLake, Lakehouse, Warehouse, Data Factory pipelines, Dataflows Gen2, Notebooks (PySpark/Spark SQL) and Real-Time Intelligence
• Build medallion architectures (Bronze/Silver/Gold), including incremental loads, change data capture, slowly changing dimensions and error handling
• Set up ingestion from diverse sources (SQL databases, APIs, files, SaaS applications, SAP, streaming sources) using pipelines, shortcuts and mirroring
• Write clean, reusable and tested code in PySpark, Spark SQL, T-SQL and KQL, optimizing Delta tables
• Add data quality checks, validation rules, logging and alerting to data pipelines
• Build enterprise semantic models (star schema) using Direct Lake, Import or DirectQuery as specified in the architecture
• Write efficient DAX measures, calculation groups and Power Query (M) transformations
• Build reports and dashboards that follow customer design guidelines and best practices
• Implement row-level and object-level security, sensitivity labels and workspace permissions as defined in the security concept
• Tune model and report performance using tools like DAX Studio, Tabular Editor, Best Practice Analyzer and Performance Analyzer

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