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Strong bank brand, Bangalore metro location, and a common data-engineer title drive high competition.
Core data engineering skills are transferable, though banking regulatory context favors finance backgrounds.
Explicit 10+ years plus mandatory Snowflake, DBT, AWS, Python, and Airflow requirements make shortlisting highly strict.
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Design, build, and maintain enterprise-scale data platforms and pipelines supporting data warehouses, operational data stores, and data marts with a focus on integration, security, governance, and performance optimization.
Lead a team of data engineers to deliver resilient, scalable data solutions including migration from legacy systems to modern platforms like Snowflake and AWS cloud services.
Coordinate design reviews, manage project timelines, risk assessments, production support, and collaborate with global technology teams to meet business objectives.
10+ years of experience in Data Engineering with expertise in data warehouse and data lake design and development.
Strong technical skills on Snowflake data platform, AWS cloud services (S3, Lambda, Glue, etc.), ELT/ETL tools (DBT, Qlik Replicate, Snowpark), SQL, Python/Unix scripting, and Airflow for orchestration.
Experience with data modeling (Logical, Physical, Dimensional, Data Vault) and performance tuning of data pipelines and database objects.
Work Experience Required: 10+ years; Job Location: Bangalore; Role Type: Hybrid. Notice period: Not explicitly mentioned in the JD.
Experienced in leading data engineering teams handling enterprise data platforms in a financial services context or similarly complex regulated environment.
Skilled in managing end-to-end data platform lifecycle including design, migration, automation, and performance tuning to support critical business functions such as Regulatory Reporting and Risk Steering.
Capable of coordinating with cross-functional and global teams, managing technical risks, and delivering timely, quality solutions in an agile engineering environment.