Description

Own the data governance lifecycle, from metadata management to quality assurance, while integrating Agentic AI and LLM applications to automate and enhance data integrity.

This role is on-site.

Responsibilities

• Maintain data catalogs and dictionaries by documenting business, technical, and operational metadata, including data lineage and definitions.
• Perform deep profiling of large datasets to identify structure, patterns, and hidden anomalies.
• Develop and implement data quality rules, checks, and preventative controls using SQL and Python.
• Design AI-powered solutions across the data quality lifecycle utilizing Agentic AI frameworks and LLM-based applications.
• Monitor data pipelines and ETL processes to proactively identify quality issues and operational anomalies.

Required Skills

• 8+ years of hands-on experience in data quality, MIS, and data management.
• Strong proficiency in Python and SQL for data manipulation and rule implementation.
• Experience with metadata management tools such as Collibra or Teradata.
• Knowledge of LLM applications, AI Agents, and LangChain.
• 2-3 years of experience in the Banking Industry.
• Ability to define and validate business rules for data completeness, accuracy, and consistency.
• Experience with data quality metrics, scorecards, and remediation action plans.

Preferred Skills

• Familiarity with SAS, LangGraph frameworks, and multi-agent orchestration.
• Domain knowledge in Banking (Cards, Deposits, Loans, Wealth Management, Insurance) and Finance Regulations.
• Experience with Tableau for dashboarding and data visualization.

Key Skills

Education

Any Graduate