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Metro location, popular data-engineer role, and broad Snowflake/DBT/AWS skillset raise applicant competition density.
Core data engineering skills are transferable, though enterprise banking context moderately favors finance-experienced candidates.
Explicit 10+ years, mandatory Snowflake/DBT/AWS/ETL expertise and finance context create strict shortlisting filters.
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Lead design, build, and maintenance of enterprise-scale data platforms, data lakes, and data warehouses with a focus on Snowflake and cloud solutions.
Develop and optimize complex data pipelines and data integration processes including ETL/ELT using tools like DBT, ensuring data security, privacy, and governance compliance.
Manage team deliverables, perform design reviews, handle project timelines, risk mitigation, coordinate with global teams, and provide production incident support.
10+ years experience in data engineering focused on Data Warehouse and Data Lake design and development.
Strong proficiency in Snowflake platform and AWS cloud services (S3, Lambda, Glue, Step Function, CloudWatch).
Expertise in ELT/ETL tools including DBT, Qlik Replicate, Snowpark, with advanced SQL, Unix, and Python scripting skills.
Work Experience Required: 10+ years in relevant data engineering roles; Location: Bangalore; Role Type: Hybrid.
Experienced lead or manager in enterprise data engineering handling large scale data platforms, pipelines, and team coordination.
Deep technical expertise in cloud data architectures (Snowflake, AWS Redshift) and data modeling (Logical, Physical, Dimensional, Data Vault).
Proven ability to work with cross-functional global teams, manage production issues, and deliver data solutions in a regulated financial services environment.