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Mid-level Bangalore Databricks data engineer; popular title and metro location increase candidate competition.
Requires Databricks/Delta Lake expertise and governance experience, moderately reducing cross-industry portability.
Explicit 5–8 years requirement plus mandatory Databricks, Spark, Unity Catalog, and governance skills tighten filters.
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Design, build, and maintain scalable ETL/ELT data pipelines on Azure Databricks following the medallion architecture (bronze to platinum layers).
Implement data governance, auditing, and operational metadata frameworks to ensure pipeline observability and compliance.
Enable cross-cloud data sharing and prepare analytics- and AI-ready datasets optimised for downstream analytics, AI/ML, and reporting consumption.
Bachelor’s degree in IT, Computer Science, Data Science, Analytics, or Statistics required.
5–8 years of experience in data engineering or analytics engineering with substantial hands-on Azure Databricks experience.
Strong skills in Spark/PySpark, SQL, building medallion-architecture pipelines on Delta Lake, and using Unity Catalog for governance.
Experience with data ingestion (streaming, connectors, Delta Sharing), cross-cloud data migration, data orchestration (Databricks Workflows/DLT), and CI/CD in data engineering contexts.
Experienced individual contributor or senior engineer skilled in complex data pipeline design and operational governance in Azure Databricks environments.
Someone familiar with data governance, data-quality frameworks, and enabling AI/ML workloads through curated data models and datasets.
Candidate with background or willingness to work with regulated financial/tax data and advanced analytics tools like Power BI or Tableau is preferred but not mandatory.