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Strong bank brand, Bangalore location, mid-level generalist Data Engineer title and popular stack increase applicant competition.
Core data engineering skills are transferable, but banking domain and Snowflake/DBT specialization moderately constrain fit.
Explicit 5+ years requirement plus mandatory Snowflake, DBT, Airflow and cloud skills make filters strict.
Design, build, and maintain enterprise-scale data pipelines and platforms including Data Warehouse, Data Lake, and cloud solutions primarily on Snowflake and AWS.
Create and optimize data ingestion pipelines from various sources (File, DB, API, SharePoint) with performance tuning and data governance considerations.
Collaborate in Agile teams to support delivery, perform impact analysis, and provide technical support for production incidents.
5+ years experience in building data pipelines in Data Warehouse and Data Lake environments.
Strong expertise in Snowflake data platform and AWS cloud services (S3, Lambda, Glue, Step Functions, CloudWatch).
Proficiency in ELT tools such as DBT and scripting languages like Python and SQL; experience with data pipeline orchestration using Airflow.
Work Experience Required: 5+ years; Location: Bangalore (Hybrid role).
Experienced data engineer with strong skills in Snowflake, DBT, and AWS cloud services specializing in enterprise-level data platform implementation and migration.
Comfortable working in Agile environments collaborating with global (primarily US) cross-functional teams with experience in end-to-end pipeline delivery and incident management.
Familiar with data modeling (Relational/Dimensional), performance tuning, and version control with Gitlab, preferably with basic financial industry exposure.