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Strong employer brand, Bangalore metro location, and a popular mid-level data-engineering role increase competition.
Core data-engineering skills are transferable, but Databricks/Azure specifics create moderate industry specificity.
Explicit 2–4 years plus mandatory Databricks, PySpark, Azure and governance skills enforce strict filters.
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Design and maintain scalable ETL/ELT pipelines using Azure Databricks to ingest and transform data into analytics-ready formats following the Medallion Architecture.
Orchestrate and monitor data workflows with Azure Data Factory or Databricks Workflows to ensure accurate and timely delivery of daily retail reports.
Implement data governance, security, and automated data quality checks to ensure secure, compliant, and accurate data handling across enterprise systems.
Bachelor’s degree in Computer Science, Data Science, or related engineering field required.
2 to 4 years of professional experience with Python (PySpark) and SQL for distributed data processing.
Proficiency with Azure cloud services including Azure Data Lake Storage Gen2, Azure Data Factory, Key Vault, and Databricks ecosystem components such as Delta Lake, Unity Catalog, and Databricks Notebooks.
Work location: Bangalore, India; Fully onsite requirement; Up to 10% travel expected.
Experienced in integrating complex data from internal ERP systems and external retail sources to optimize supply chain and analytics pipelines.
Comfortable operating within the Databricks environment with practical skills in Spark architecture, Delta Lake's ACID features, and cloud data governance.
Familiar with agile development practices and collaborating in cross-functional teams to design scalable, reliable, and secure data engineering solutions.