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Tier-1 brand, metro location, mid-level data engineer role with popular skills increases competition.
Core data engineering skills transfer across industries, though financial domain familiarity mildly biases fit.
Multiple mandatory technical skills (Snowflake, ETL, data modelling) plus senior AVP expectations make filters strict.
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Design, develop, optimize, and maintain scalable ETL pipelines and data models on Snowflake for large-scale data processing.
Ensure high data quality, consistency, and availability while performing root cause analysis and leading production support for critical data pipelines.
Leverage AI-assisted engineering tools to enhance productivity in writing SQL, designing ETL pipelines, debugging, and automating validation tasks.
Strong expertise in SQL and hands-on experience with Snowflake for ETL and data modelling.
Solid experience with relational databases: SQL Server, Oracle, and PostgreSQL.
Work Experience Required: Not explicitly mentioned in the JD.
Location: Bangalore, India.
Experienced in designing dimensional data models (star schema, snowflake schema) and implementing Slowly Changing Dimensions for analytical use cases.
Proven ability to independently handle complex data engineering problems with ownership of end-to-end data pipelines and solutions.
Operates effectively in Agile environments with strong collaboration skills, mentoring junior engineers, and working cross-functionally with architects and business stakeholders.