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Strong bank brand, Bangalore location, and a generalist Data Engineer role increase applicant competition.
Data engineering skills are transferable, but banking domain and Snowflake focus moderately increase specialization.
Specific Snowflake, data modelling and ETL expertise required by a regulated bank increases filtering stringency.
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Design, build, and optimize scalable ETL data pipelines and dimensional data models on Snowflake for large-scale data processing.
Ensure data quality, availability, and integrity across multiple upstream and downstream systems, including root cause analysis and production support for critical pipelines.
Leverage AI tools to enhance development productivity, and collaborate with architects and business teams to align solutions with enterprise data architecture.
Strong expertise in Snowflake, advanced SQL, and ETL pipeline design and optimization.
Experience with relational databases like SQL Server, Oracle, and PostgreSQL.
Demonstrated experience in data modelling concepts such as star schema, slowly changing dimensions (SCD), and dimensional modelling.
Work Experience Required: Not explicitly mentioned in the JD. Location: Bangalore, India.
Proven ability to own end-to-end data engineering and modelling responsibilities, including troubleshooting and performance tuning at scale.
Experience working with complex multi-database environments and familiarity with cloud data platform concepts, particularly Snowflake and GCP.
Experience leading and mentoring junior engineers, and acting as a technical lead interfacing between data engineering and architecture teams.