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Mid-level requirement, metro location, but niche Fabric specialization limits applicant pool.
Azure/Microsoft Fabric specificity limits portability, though core PySpark and data engineering skills remain transferable.
Explicit 5+ years plus 1–2 years Fabric and mandatory PySpark/SQL skills create strict filters.
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Design and develop scalable ETL/ELT data pipelines using Microsoft Fabric components such as Data Factory, Dataflows Gen2, and Notebooks.
Manage and optimize OneLake storage and implement Medallion architecture (Bronze/Silver/Gold) to ensure data quality and performance across Lakehouse and Warehouse environments.
Collaborate with leads and architects to implement data governance, security policies, and automate deployments using Git, Azure DevOps, or GitHub pipelines.
5+ years of overall data engineering experience including 1–2 years of hands-on Microsoft Fabric experience covering Lakehouse, Warehouse, OneLake, and Data Factory.
Expert-level SQL and strong proficiency in PySpark for large-scale data processing and transformation.
Bachelor’s or Master’s degree in Computer Science, IT, or related Engineering field.
Solid understanding of Azure data services including ADLS Gen2, Azure SQL, Key Vault, and experience with Git-based version control and CI/CD deployments.
Demonstrated ability to independently deliver complex data engineering solutions within the Microsoft Fabric ecosystem.
Experience implementing dimensional models and Lakehouse architectural patterns for enterprise-scale data platforms.
Familiarity with data governance and security frameworks using Microsoft Purview and collaborative agile/team pod environments.