Data Governance with AI/Gen AI
Data Governance with AI/Gen AI
ROLE
– Maintain Data Catalog/Dictionary: Document and maintain business, technical, and operational metadata, including data lineage, definitions, and data standards
– Data Lineage Mapping: Utilize metadata to map data lineage, understanding how data flows from source systems to downstream reporting to identify potential impact areas
– Policy Compliance: Ensure all data assets adhere to defined data governance policies and data privacy regulations
– Profiling Execution: Perform deep profiling of large datasets to understand data structure, patterns, and content, identifying hidden anomalies or missing information
– Rule Definition: Collaborate with business stakeholders to define and validate business rules for data validation
– Rule Authoring/Implementation: Develop and implement data quality rules, checks, and preventative/detective controls using SQL, Python, or specialized DQ tools
– Continuous Monitoring: Actively monitor data pipelines, ETL processes, and dashboards to proactively identify DQ issues and operational anomalies
– Issue Resolution: Identify, document, and triage data quality issues through a tracking system
– Remediation Action Plans: Develop and execute remediation plans, including data cleansing efforts and automated corrections
– Cross-Functional Collaboration: Partner with data stewards, IT, and developers to resolve data issues and implement long-term solutions
– Design and Develop AI powered solution across data Quality lifecycle utilizing Agentic AI frameworks
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
– Audit Framework
– Data quality framework
– Risk & control Metrics
– 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
– Mentoring junior members in the team
– 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
– BTech / B.E in Information Technology / Information Systems / Computer Applications
– Post Graduate in – Computer Science, Mathematics, Operations Research, Econometrics, Management Science and related fields
– 8+ years of hands-on experience in people management, delivering data quality, MIS, data management with at least 2-3 years’ experience in Banking Industry
