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Tier-1 bank brand plus Bengaluru metro increase candidate density, but senior niche data governance reduces competition.
Core data quality skills are transferable, but banking, audit, and regulatory experience raise industry specificity.
Explicit 9+ years, managerial responsibility, banking domain and specific tech stack make shortlisting stringent.
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Own the development and execution of enterprise-wide data quality measurement programs across retail consumer banking data.
Design, develop, and deploy scalable AI-powered data quality solutions including LLM-based applications and AI agents to enhance workflows and decision-making.
Manage metadata, ensure data governance compliance, perform root cause analysis for data issues, and lead remediation efforts in collaboration with cross-functional teams.
9-10+ years of experience with hands-on data quality, management, and MIS; minimum 2-3 years in banking domain.
Advanced degree: MBA/Masters in Economics, Statistics, Mathematics, IT, Computer Applications, or related; BTech/BE preferred.
Technical skills including Python, SQL, SAS, Teradata, Collibra; experience with prompt engineering and LLM-based AI applications.
Work Experience Required: 9-10+ years including banking; Notice period: Not explicitly mentioned in the JD.
Experienced leader combining strong software engineering and AI/ML skills with deep domain knowledge in banking products like cards, deposits, loans, wealth management, and insurance.
Proven capability to manage data governance frameworks, data quality rule authoring, and end-to-end remediation in complex, regulated environments.
Demonstrates strategic thinking through AI-driven process automation and ability to collaborate with stakeholders across IT, business, and audit functions.