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Strong employer brand, popular data-engineer title, and Bangalore location increase competition density.
Data engineering skills transferable across industries but Azure/Databricks/OpenShift focus adds moderate specialization.
Many mandatory technical skills (Databricks, PySpark, Azure, OpenShift, CI/CD) create strict screening filters.
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Design, build, and optimize scalable ETL/ELT data pipelines using Python and PySpark within Azure Databricks and Azure Data Factory.
Develop data ingestion and streaming data extraction processes using sources like Kafka and Azure Event Hubs, ensuring data quality and monitoring with tools like Grafana.
Manage cloud infrastructure on OpenShift and Azure, implementing CI/CD pipelines using GitHub Actions, and optimize SQL queries and data models for performance.
Proven experience designing, building, and maintaining ETL/ELT data pipelines using Python, PySpark, Azure Databricks, and Azure Data Factory.
Strong SQL skills with experience in complex queries, schema design, and optimization.
Hands-on experience with CI/CD pipelines (GitHub Actions), OpenShift, HELM, and monitoring tools like Grafana.
Work Experience Required: Not explicitly mentioned in the JD.
Experienced in Azure data ecosystem and cloud data platform management, including analytics and security services.
Able to manage end-to-end data pipeline delivery with strong focus on performance optimization and automation.
Familiar with real-time data processing (Kafka, Azure Event Hubs) and container orchestration in enterprise environments.