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Mid-level generalist title, metro location, and broad cloud/data skillset increase applicant competition.
Core data engineering skills like SQL, Python and dbt are broadly transferable across industries.
Explicit 4–7 years requirement plus mandatory SQL, Python and cloud data tooling makes shortlisting strict.
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Develop and maintain end-to-end data ingestion pipelines from diverse data sources.
Build analytical data marts by processing and joining datasets to support business functions.
Optimize query performance and storage costs using BigQuery partitioning, clustering, and materialized views; manage data governance including cleaning and access control.
4 to 7 years of experience in data engineering or data infrastructure roles.
Proficiency in SQL, Python, and cloud-native data tools such as Plx, dbt, or equivalents.
Experience handling structured and semi-structured data at scale.
Location requirement: Bengaluru, Karnataka, India.
Has strong technical skills in building and optimizing scalable cloud data pipelines and analytical marts.
Experienced in data governance practices including data quality, annotation, and access control.
Able to translate business processes into technical data structures and perform root-cause analysis for pipeline issues.