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Mid-level generalist data engineer title and common 3-5 years range increase candidate density.
Data engineering skills are transferable but Azure/Microsoft Fabric specificity creates moderate industry fit sensitivity.
Explicit 3-5 years and many mandatory technical stack and governance requirements create strict shortlisting.
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Design, build, and maintain efficient ETL/ELT pipelines using Medallion architecture to ensure data quality and scalability.
Collaborate with Data Architecture and cross-functional teams to deliver governed, enterprise-aligned data solutions supporting BI and analytics.
Maintain hybrid data environments (SQL Server, Azure Synapse, Microsoft Fabric), implement monitoring, data governance, and continuous process improvements.
3–5 years of experience in data engineering or a similar technical role.
Strong proficiency in SQL and advanced skills in Python, PySpark, and C# for data processing and pipeline development.
Hands-on experience with Microsoft Fabric components and Azure data services (ADF, ADLS, Synapse, Databricks, Azure SQL).
Work Experience Required: 3–5 years in data engineering or similar role.
Experienced in implementing and operating scalable data pipelines applying Medallion architecture in a hybrid cloud environment.
Skilled in collaborating across data architecture, BI teams, and stakeholders to deliver governed and compliant data solutions.
Proficient in modern CI/CD and DevOps practices for data engineering in fast-paced cloud ecosystems.