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Known brand, mid-level generalist title, metro Bangalore and common PySpark/Azure skillset increase applicant competition.
Role requires Azure/Databricks-specific experience, moderately limiting cross-industry mobility.
Explicit 4+ years requirement and mandatory PySpark/Azure/Databricks skills make filtering stringent.
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Design, build, and optimize Azure-based ETL/ELT data pipelines using PySpark and Spark SQL in Databricks environment.
Implement and manage hybrid data integration between on-premise databases and Azure using ADF, HVR/Fivetran, and secure network configurations.
Ensure data pipeline reliability through root cause analysis, troubleshooting, and support of CI/CD and version control processes.
Bachelor's degree in Computer Science, Engineering, or related field.
Minimum 4 years of hands-on experience in data pipeline development and data engineering.
Proficiency in PySpark, Spark SQL, and Azure cloud services including ADF, Databricks, and ADLS.
Experience with SQL, data modeling, Git, and CI/CD pipelines; familiarity with agile practices.
Strong experience in cloud-native data engineering within Azure ecosystem focusing on scalable, cost-efficient ETL/ELT pipelines.
Proven ability to collaborate with cross-functional teams including data analysts and scientists to meet complex data requirements.
Operational focus on performance tuning, data governance, and automation to ensure high-quality, reliable data solutions.