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Tier-1 brand, mid-level popular Data Engineer role in Bangalore with broad Azure/PySpark requirements increases competition.
Requires Azure Databricks, PySpark, and OpenShift expertise, making cross-industry moves moderately transferable.
Explicit 6–8 years plus mandatory Azure, PySpark, Databricks and OpenShift skills imply high filtering.
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Design, build, and optimize scalable ETL/ELT data pipelines using Python, PySpark within Azure Databricks and Azure Data Factory.
Develop and maintain data ingestion from multiple sources, ensuring data quality via monitoring, alerting, and dashboarding solutions like Grafana.
Manage cloud infrastructure setup and deployment on OpenShift including CI/CD pipeline automation using GitHub Actions and application packaging with HELM.
6-8 years of relevant experience in data engineering or related domain.
Proficiency in Python and PySpark for large-scale ETL development.
Hands-on experience with Azure Data Factory, Azure Databricks, Azure SQL Server, and Azure Key Vault.
Experience with OpenShift container orchestration and CI/CD pipelines using GitHub Actions; experience with Grafana for monitoring.
Experienced in end-to-end data pipeline development with strong focus on performance optimization and complex SQL querying.
Comfortable operating in Azure cloud ecosystem integrating multiple analytics services and employing DevOps best practices.
Capable of managing containerized deployments on OpenShift leveraging HELM and monitoring solutions, suited for collaborative multi-team environments.