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Tier-1 bank and metro location with senior, niche data+AI requirements produce moderate competition.
Strong banking governance, audit, and domain requirements limit transferability across industries.
Explicit 10+ years, banking experience and technical/education mandates create high shortlisting strictness.
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Own and manage enterprise data quality measurement programs and data governance including metadata management, data lineage, and data ownership within retail consumer bank.
Design, develop, and deploy AI-powered solutions using Agentic AI frameworks and LLM-based applications to enhance data quality lifecycle and enterprise workflows.
Lead data profiling, root cause analysis, data quality rule creation, continuous monitoring, issue remediation, and audit support to ensure data accuracy, completeness, and policy compliance.
10+ years of hands-on experience in data quality, MIS, data management with at least 7+ years in Banking Industry.
Educational background: MBA/Masters in Economics, Statistics, Mathematics, IT, Computer Applications, Engineering from premier institute; BTech/BE in IT/IS/Computer Applications preferred.
Technical proficiency in Python, SQL, SAS, Teradata, Collibra, and experience with prompt engineering, LLM-based applications, AI agents, LangChain/LangGraph frameworks.
Work Experience Required: 10+ years in data management domain with Banking sector experience explicitly mentioned.
Experienced in managing large-scale data governance and quality programs in banking domain including Cards, Deposits, Loans, Wealth management, and Insurance.
Strong software engineering and AI skillset with hands-on experience in machine learning, generative AI, and autonomous workflows.
Strategic operator comfortable leading cross-functional teams, driving complex problem resolution, audit compliance, and building scalable data-driven solutions.