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Strong Tier-1 brand, metro Bangalore, and a visible mid-level data-engineer role increase applicant competition.
Core data engineering skills are transferable across industries, though Azure/Microsoft Fabric specialization moderately limits portability.
Explicit 5–10 years requirement plus mandatory Azure/Microsoft Fabric skills and preferred certifications increases strictness.
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Design, develop, and maintain scalable data pipelines and integration solutions using Azure Data Factory and Microsoft Fabric.
Build and optimize Lakehouse and Data Warehouse solutions leveraging PySpark, Spark SQL, Python, and medallion architecture.
Collaborate cross-functionally to ensure data quality, security, governance, and to deliver high-quality data platforms for business insights.
5-10 years of hands-on experience in data engineering and analytics.
Proficiency with Azure Data Services (Azure Data Factory, Synapse Analytics, ADLS Gen2, Azure SQL Database) and Microsoft Fabric workloads (Lakehouse, Data Warehouse, Data Pipelines).
Strong programming skills in PySpark, Spark SQL, Python, and SQL.
Educational qualification: BE/B.Tech/ME/M.Tech/MBA/MCA with at least 60% marks.
Experienced with implementing medallion architecture and Delta Lake/lakehouse approaches.
Holds or is willing to obtain Azure Data Engineer Associate (DP-203) and Microsoft Fabric Analytics Engineer Associate (DP-600/DP-700) certifications.
Familiarity with CI/CD pipelines, Agile/Scrum environments, and data governance best practices.