Description

You will own data governance, quality, and metadata management for enterprise systems, integrating Agentic AI and Gen AI solutions to automate workflows and enhance decision-making.

This role is on-site.

Responsibilities

• Document and maintain business, technical, and operational metadata, including data lineage, definitions, and standards to map data flow from source systems to downstream reporting.
• Perform deep profiling on large datasets to identify structure, patterns, and hidden anomalies, investigating root causes of data quality issues.
• Develop and implement data quality rules, checks, and preventative controls using Python and SQL, ensuring adherence to governance policies and privacy regulations.
• Design, develop, and deploy scalable AI-powered solutions, including LLM applications and AI agents, to enhance enterprise workflows and operational efficiency.
• Collaborate with business stakeholders and data stewards to validate business rules, monitor pipelines, and resolve data issues sustainably.

Required Skills

• 8+ years of hands-on experience in data quality, MIS, data management, and people management.
• Strong proficiency in Python and SQL for data profiling, pipeline monitoring, and control implementation.
• Deep expertise in Data Governance, Metadata Management, and Data Quality frameworks.
• Experience with LLM Applications, AI Agents, and Machine Learning concepts.
• Hands-on experience with Collibra and Teradata.
• Minimum 2-3 years of experience in the Banking industry.

Preferred Skills

• Knowledge of LangChain/LangGraph, Multi-agent orchestration, and SAS.
• Familiarity with Tableau, Prompt Engineering, and Banking domain knowledge (Cards, Deposits, Loans, Wealth, Insurance).
• Understanding of Audit Frameworks, Risk & Control Metrics, and Finance Regulations.

Key Skills

Education

Any Graduate