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Bengaluru mid-level Data Engineer at known brand with common Azure/PySpark stack increases competition.
PySpark, Databricks and Azure skills are broadly transferable across industries.
Explicit 6+ years and mandatory Azure, Databricks, and PySpark skills create strict shortlisting filters.
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Design, develop, and optimize Azure-based ETL/ELT data pipelines using PySpark, Spark SQL, and Databricks.
Build and orchestrate data workflows integrating on-premise databases with Azure cloud services using ADF, HVR/Fivetran, ensuring data quality and governance.
Collaborate with data analysts, scientists, and business teams to meet data requirements and maintain CI/CD automation and pipeline reliability.
6+ years of experience in data pipeline development and data engineering.
Proficiency in PySpark, Spark SQL, Azure services (ADF, Databricks, ADLS), and SQL.
Bachelor's degree in Computer Science, Engineering, or related field.
Experience with version control (Git) and CI/CD pipelines; work experience in cloud-native data engineering.
Experienced in building scalable data solutions on Azure cloud platforms with strong expertise in Databricks and related Azure Data Services.
Demonstrates ability to optimize Spark jobs for performance, scalability, and cost efficiency in enterprise environments.
Familiar with hybrid cloud data integration tools and real-time streaming solutions, comfortable collaborating across functional teams to deliver data solutions.