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Pan-India hybrid recruitment, mid-level 4–7 year band, and popular data engineering role increase candidate density.
Core cloud data engineering skills transfer across industries, but Azure/Databricks specialization moderately limits portability.
Explicit 4–7 year requirement plus mandatory Azure Databricks, PySpark, ADF, Delta Lake, and CI/CD skills raise filtering rigor.
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Design, develop, and maintain end-to-end scalable data pipelines on Azure using Azure Databricks, Azure Data Factory, and related Azure data services.
Build and optimize Lakehouse architectures, Delta Lake-based data models, and transformation frameworks to support enterprise data needs.
Implement data governance, CI/CD pipelines, troubleshooting, and collaborate with stakeholders including analytics and AI teams to deliver curated data solutions.
4–7 years of relevant experience in data engineering.
Proficiency with Azure Databricks, PySpark, Spark SQL, Azure Data Factory, and ADLS Gen2 mandatory.
Bachelor's degree in B.E./B.Tech/MCA or equivalent required.
Work Mode: Hybrid; Location: Pan India; Notice Period: Not explicitly mentioned in the JD.
Experienced in building scalable ETL/ELT systems and Lakehouse architectures using Azure data platform technologies.
Skilled at performance tuning, data quality enforcement, CI/CD via Azure DevOps, and managing data governance.
Capable of collaborating cross-functionally with business stakeholders, data scientists, and analytics teams in enterprise environments.