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Tier-1 brand, common data-engineer title, mid-level profile and Pune metro drive high competition.
Core data engineering skills are transferable, though banking risk and controls increase domain specificity.
Moderate technical stack requirements (Python, AWS, PySpark) but no explicit years yields medium strictness.
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Build and maintain data architectures including data pipelines, warehouses, and lakes ensuring data durability, accuracy, accessibility, and security.
Develop data processing and analysis algorithms suitable for complex data volumes and collaborate with data scientists to deploy machine learning models.
Lead and supervise a team, manage operational processing end-to-end, embed risk mitigation policies, and influence decision-making within the area of expertise.
Experience with AWS, Python, pySQL, and pySpark is mandatory.
Work Experience Required: Not explicitly mentioned in the JD.
Role requires leadership skills including team supervision and resource allocation or demonstrated technical expertise as an individual contributor.
Location: Pune, India.
Experienced in building scalable, secure data architectures and processing algorithms in AWS cloud environment.
Capable of leading teams or acting as a technical advisor with strong risk management and control focus.
Familiar with CI/CD pipelines and Snowflake platform is a plus, indicating readiness for advanced data engineering in a digital transformation context.