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Tier-1 brand, metro location, and common data tooling increase applicant density moderately.
Core data engineering skills are transferable, though banking risk and controls increase domain specificity.
Specific data engineering skills and leadership required, but no explicit years, so moderately strict.
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Own the build and maintenance of data pipelines, data warehouses and data lakes ensuring accuracy, accessibility, and security of data.
Design and implement data architectures and processing algorithms suited to data volume and complexity, enabling reporting, insight generation, and collaboration with data scientists on ML model deployment.
Contribute to or set strategic direction, manage resources and budgets, and provide technical leadership or subject matter expertise, including risk and control management and advising senior stakeholders.
Experience building and maintaining data pipelines and datasets for reporting and insights.
Proficiency with ETL tools such as Alteryx (or equivalent) and visualization tools like Tableau (or equivalent).
Strong SQL skills and data modelling experience; knowledge of operating SQL databases is required.
Work Experience Required: Not explicitly mentioned in the JD; Location requirement: Pune.
Experienced in cloud data engineering with AWS and modern data ecosystems (e.g., Snowflake) and familiar with data orchestration and modern lake/lakehouse architectures.
Capable of independent requirement gathering and clear stakeholder communication with strong documentation skills.
Demonstrates strategic thinking with cross-functional collaboration skills, capable of managing technology-driven change and leading risk and control governance initiatives.