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Tier-1 brand, metro location, mid-level generalist data role, and broad skillset increase candidate competition.
Banking domain knowledge, audit/regulatory and data governance expertise make background fit highly sensitive.
Specific years, domain (data governance) experience, banking exposure and technical stack requirements make shortlisting strict.
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Manage and maintain data governance standards including metadata management, data lineage mapping, and ensuring policy compliance.
Profile large datasets to identify data quality issues, create and implement data quality rules, and develop remediation plans to ensure data accuracy and completeness.
Design, develop, and deploy AI-powered solutions and automation frameworks to enhance data quality processes and workflows.
2 to 5 years of experience in data quality, MIS, or data management with at least 1 year in the banking industry.
Proficiency in Python, SQL, SAS, Teradata, and experience with data governance tools (e.g., Collibra).
Master's degree (MBA or in fields like Economics, Statistics, Mathematics, IT, Computer Science, or related areas); BTech/BE preferred in IT or related fields.
Not explicitly mentioned in the JD: Notice period or strict onsite/location requirements.
Experienced in banking or financial domain with a focus on data governance and data quality frameworks.
Strong technical background combining software engineering and AI/ML, including experience with LLM-based applications and agentic AI frameworks.
Capable of collaborating across multiple functions, managing cross-team data quality issue resolutions, and communicating complex issues to senior management.