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Mid-level metro Data Engineer role with generalist skills and broad Azure/Microsoft Fabric requirements increases competition.
Core data engineering skills are transferable, but Microsoft Fabric/Azure specialization limits cross-industry fit.
Explicit 5–7+ years plus mandatory Azure/Microsoft Fabric, Python, SQL and PySpark skills increases strictness.
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Design, build, and enhance scalable batch and near-real-time data pipelines using Microsoft Fabric and Azure cloud components.
Implement data products with embedded data quality checks, metadata enrichment, certification workflows, and lineage capture to ensure trusted data.
Collaborate cross-functionally with architects, analysts, scientists, governance, and security teams to deliver robust, compliant, and high-performing data solutions.
5 to 7+ years of professional experience in data engineering or related cloud data roles.
Hands-on expertise with Microsoft Fabric components (Lakehouse, Warehouse, Pipelines, Notebooks, OneLake, Dataflows).
Strong programming/query skills in SQL, Python, and PySpark; knowledge of KQL is a plus.
Experience delivering production-grade data pipelines in Azure or similar cloud environments; experience with agile delivery practices.
Proven ability to create reusable and scalable ELT/ETL ingestion, transformation, and orchestration patterns supporting analytics and AI.
Experience working in regulated, enterprise-scale, or multi-domain data environments with familiarity in data governance and Microsoft Purview.
Comfortable optimizing platform performance, reliability, and cost across storage, compute, and pipeline execution within Azure ecosystems.