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Tier-1 employer, metro location, and broad data engineering requirements increase candidate competition.
Core data engineering skills are transferable, though banking compliance and domain knowledge moderately restrict fit.
Mandatory Snowflake, Python, CI/CD, big-data and regulated bank controls make hiring filters stringent.
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Build and maintain production-grade data infrastructure primarily on Snowflake integrated with broader data stack including AWS components.
Develop, automate, and monitor data pipelines ensuring data quality, CI/CD, and environment promotion across dev/test/prod.
Collaborate with stakeholders to onboard data, build analytical data models, support research analysts and BI/data science users, and productionize models and analyses.
Strong hands-on experience with Snowflake, SQL, and Python for data engineering tasks.
Experience in data pipelining, automation, and CI/CD practices for data platforms and environment promotion.
Familiarity with AWS big data tools (Athena, Presto, Spark) and source control using git in team environments.
Work Experience Required: Not explicitly mentioned in the JD; Location: Mumbai, India.
Experienced in building scalable data infrastructure in financial or research-driven environments with Snowflake and AWS data stacks.
Skilled in managing cross-functional collaboration with IT, vendors, and business stakeholders to continuously improve data solutions.
Capable of designing analytical data models and maintaining high data quality with observability and automation in competitive production environments.