ROLE
– Manage the implementation of best-in-class data quality measurement programs across the globe in retail consumer bank
– Support Data Governance: Standardization of data definitions and ensuring consistency in usage as per definitions across systems/products/regions
– Support Meta Data Management: Leveraging data lineage, data discovery initiatives and creation of enterprise level meta data for all retail consumer products
– Support Data Ownership: Identifying trusted data sources, data owners and consumers across process and products
– Support Issue Management: Identifying defects and investigating root causes for different issues
– Support Audit Support: Identifying cases on control gaps, policy breaches and providing data evidence for audit completion
– Support Data Certification: Developing procedures on data certification and certifying as per fit for purpose criteria
– Profile data to identify flaws, author data quality rules to prevent issues, monitor data pipelines, manage metadata and remediate data concerns
– Design, develop, and deploy scalable AI-powered solutions that enhance enterprise workflows and decision-making
– Maintain Data Catalog/Dictionary: Document and maintain business, technical, and operational metadata, including data lineage, definitions, and data standards
– Perform data lineage mapping, policy compliance, data profiling and analysis
– Create and author data quality rules, develop and implement data quality rules, checks, and preventative/detective controls
– Monitor data pipelines, ETL processes, and dashboards to proactively identify DQ issues and operational anomalies
– Develop and maintain data quality metrics and scorecards to report on data accuracy trends to leadership
– Identify, document, and triage data quality issues through a tracking system
– Develop and execute remediation plans, including data cleansing efforts and automated corrections

REQUIREMENTS
– Proficient in Python, SAS, SQL, Teradata, Collibra
– Experience with prompt engineering
– Experience building LLM-based applications, AI agents, or autonomous workflows
– Exposure to LangChain / LangGraph frameworks
– Exposure to creating multi-agent orchestration
– Exposure to BI tools and technologies – example: Tableau
– Automation and process re-engineering / optimization skills
– Knowledge of Finance Regulations, Understanding of Audit Process
– Ability to identify, clearly articulate and solve complex business problems and present them to the senior management or partners in a structured and simpler form
– Excellent communication and inter-personal skills
– Good process/project management skills
– Ability to work well across multiple functional areas
– Ability to thrive in a dynamic and fast-paced environment
– MBA / Masters Degree in Economics / Statistics / Mathematics / Information Technology / Computer Applications / Engineering from a premier institute
– 10+ years of hands-on experience in people management, delivering data quality, MIS, data management with at least 2-3 years’ experience in Banking Industry