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Mid-level generalist data engineer with common Azure/PySpark skillset, leading to high applicant competition.
Core data engineering skills transferable, but Microsoft Fabric and Azure focus increases domain-specific bias.
Explicit 3–5 years plus mandatory Azure, PySpark, SQL, and Fabric skills enforce strict screening.
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Design, build, and maintain scalable ETL/ELT pipelines across on-premises and cloud platforms (SQL Server, Azure Synapse, Microsoft Fabric).
Implement Medallion architecture (Bronze, Silver, Gold layers) to enhance data quality and scalability.
Collaborate with Data Architecture, BI Engineers, and data source owners to deliver governed, reliable data solutions aligned with enterprise standards.
3–5 years of experience in data engineering or similar technical role.
Strong proficiency in SQL, Python, PySpark, and C# for data processing and pipeline development.
Experience with Microsoft Fabric components (Lakehouse, Warehouse, Pipelines, Notebooks) and Azure data services (ADF, ADLS, Synapse, Databricks, Azure SQL).
Experience working with structured, semi-structured, and unstructured data; understanding of data governance, quality, and CI/CD processes.
Experienced in developing modular data pipelines using Medallion architecture within hybrid cloud environments.
Skilled in implementing monitoring, alerting, and data quality controls to ensure data reliability and governance compliance.
Collaborates effectively across teams to translate business requirements into technical data solutions supporting self-service BI and analytics.