Data Quality / Metadata & Data Lineage Analyst

Manage and implement data quality measurement programs across retail consumer banking globally, focusing on data governance, metadata management, and data ownership.

Design, develop, and deploy AI-powered solutions (including LLM-based applications and AI agents) to enhance data quality lifecycle and enterprise workflows.

Monitor data pipelines, author data quality rules, perform root cause analysis of data issues, and drive remediation plans collaborating with cross-functional teams.

Work Experience Required: 2 to 5 years in data quality, MIS, data management with at least 1 year in Banking Industry.

Educational Requirement: MBA or Masters in Economics, Statistics, Mathematics, IT, Computer Applications, or Engineering; BTech/B.E in IT/Information Systems/Computer Applications; postgraduate degrees in related fields preferred.

Technical Skills: Proficiency in Python, SAS, SQL, Teradata, Collibra; experience with LLMs, AI agents, prompt engineering; exposure to LangChain/LangGraph and BI tools (e.g., Tableau).

Domain Knowledge: Understanding of Banking domains (Cards, Deposit, Loans, Wealth management, Insurance), audit and data quality frameworks, risk and control metrics.

Experienced in banking data environments with proven delivery of data quality and governance solutions in complex settings.

Strong software engineering background combined with hands-on expertise in machine learning, generative AI, and autonomous AI workflows relevant to data management.

Capable of collaborating across business and IT stakeholders to translate complex data governance requirements into scalable, automated solutions.