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Mid-level, popular Data Engineer title plus 3–5 years and generalist skillset increases competition.
Core data engineering skills transfer widely, though Azure/Microsoft Fabric specificity raises sensitivity moderately.
Explicit 3–5 years plus mandatory Azure, Fabric, PySpark, SQL, Python and C# raises shortlisting strictness.
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Design, build, and maintain efficient ETL/ELT pipelines implementing Medallion architecture (Bronze, Silver, Gold layers) to ensure modularity, scalability, and data quality.
Collaborate with Data Architecture and cross-functional teams to deliver governed, reliable, and scalable data solutions across hybrid data environments (SQL Server, Azure Synapse, Microsoft Fabric).
Implement monitoring, data quality processes, governance compliance, and maintain technical documentation to support data pipeline performance and accuracy.
3–5 years of experience in data engineering or a similar technical role.
Strong proficiency in SQL, Python, PySpark, and C# for data processing, transformation, and pipeline development.
Experience with Microsoft Fabric components (Lakehouse, Warehouse, Pipelines, Notebooks) and Azure data services (ADF, ADLS, Synapse, Databricks, Azure SQL).
Familiarity with data governance, CI/CD processes, version control, and cloud-based data engineering environments.
Experienced in handling complex, multi-layered data architecture using Medallion approach and hybrid cloud/on-prem environments.
Capable of collaborating effectively with diverse technical and business stakeholders to translate requirements into scalable data solutions.
Comfortable working in fast-paced cloud environments with strong attention to detail and familiarity with DevOps best practices for data pipelines.