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Tier-1 bank, mid-level Databricks/Python data engineer in Bangalore, strong applicant competition.
Databricks/Spark skills transfer broadly, but financial services governance preference raises domain specificity.
Mandatory Databricks, Python, Spark and cloud experience plus data governance needs tighten shortlisting.
Build and optimize scalable data pipelines and transformation workflows on Databricks using Python and Spark to support business insights and AI enablement across Securities Services.
Collaborate with Data Architects and Business Analysts to design robust data models and deliver compliant, business-driven data solutions.
Implement data quality checks, document ETL logic, and maintain transparency via Jira tracking; ensure governance and privacy standards compliance through dataset and pipeline registration.
Proven experience developing data pipelines and solutions on Databricks using Python (including pandas) and Spark.
Understanding of ETL concepts, data modelling, pipeline design, and cloud data platforms.
Ability to document data flows and transformation logic clearly and use Jira for project tracking.
Work Experience Required: Not explicitly mentioned in the JD.
Experienced with data engineering in financial services or large enterprise environments, particularly on cloud data platforms.
Comfortable collaborating with Data Architects and Business Analysts to translate business requirements into technical solutions.
Skilled in maintaining data governance, privacy, and compliance within complex data environments.