Senior Data Quality and Governance Analyst – Assistant Vice President

Citigroup Inc.; Chennai District; On-site; INR 1,800,000 - 3,000,000; Full time

Job summary

Citigroup Inc. is seeking a Senior Data Governance & AI Solutions Analyst to ensure data accuracy, completeness, and reliability across enterprise data assets.

You will profile data, author quality rules, monitor pipelines, and remediate data concerns while designing scalable AI-enabled workflows. The ideal candidate combines software engineering with ML/AI experience, including LLM-based applications, and will collaborate across data stewards, IT, and analytics teams within a Banking

Qualifications

• Experience in data governance, metadata management, and data quality initiatives.
• Experience designing and deploying AI-powered data solutions across lifecycle.
• Hands-on with data profiling, lineage, and quality rule authoring.

Responsibilities

• Maintain Data Catalog/Dictionary with metadata, lineage, definitions.
• Map data lineage from source systems to reports.
• Develop data quality rules and validation logic.

Skills

Python

SAS

SQL

Teradata

Collibra

Prompt engineering

LLM‑based applications

LangChain

LangGraph

Tableau

Automation

Education

MBA / Masters in Economics / Statistics / Mathematics / IT / CA / Engineering

BTech / BE in IT / IS / CA

Post Graduate in Computer Science, Math, OR Econometrics

Tools

LangChain

LangGraph

Tableau

Job description

What do we offer

• Data Governance: Standardization of data definitions and ensuring consistency in usage as per definitions across systems/products/regions.
• Meta Data Management: Leveraging data lineage, data discovery initiatives and creation of enterprise level meta data for all retail consumer products
• Data Ownership: Identifying trusted data sources, data owners and consumers across process and products
• Issue Management: Identifying defects and investigating root causes for different issues. Following up with stakeholders and creation of plan for resolution as per SLA
• Audit Support: Identifying cases on control gaps, policy breaches and providing data evidence for audit completion
• Data Certification: Developing procedures on data certification and certifying as per fit for purpose criteria

Expertise Required

Data/Information Mgt Sr Analyst is responsible for ensuring the organization’s data is accurate, complete, consistent, and reliable to support strategic planning and operational efficiency. This role involves profiling data to identify flaws, authoring data quality rules to prevent issues, monitoring data pipelines, managing metadata and remediate data concerns. This person will also be responsible to design, develop, and deploy scalable AI‑powered solutions that enhance enterprise workflows and decision‑making. The ideal candidate will combine strong software engineering skills with hands‑on experience in machine learning and generative AI systems, including LLM‑based applications and AI agents.

Metadata Management and Data Governance

• 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.

Data Profiling and Analysis

• Profiling Execution: Perform deep profiling of large datasets to understand data structure, patterns, and content, identifying hidden anomalies or missing information.
• Root Cause Analysis (RCA): Investigate data quality issues to determine the root cause, distinguishing between upstream processing errors and data entry errors.
• Data Assessment: Evaluate critical data elements (CDEs) for accuracy and completeness.

Data Quality Rule Creation and Authoring

• Rule Definition: Collaborate with business stakeholders to define and validate business rules for data validation (e.g., completeness, accuracy, consistency, validity).
• Rule Authoring/Implementation: Develop and implement data quality rules, checks, and preventative/detective controls using SQL, Python, or specialized DQ tools.
• Validation Logic: Document validation logic and exception‑handling procedures for critical datasets.

Data Monitoring and Reporting

• Continuous Monitoring: Actively monitor data pipelines, ETL processes, and dashboards to proactively identify DQ issues and operational anomalies.
• DQ Dashboards/Scorecards: Develop and maintain data quality metrics and scorecards to report on data accuracy trends to leadership.
• Alerting: Set up automated alerts for breach of data quality thresholds.

Data Concern Remediations

• 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

Technical Skills

• 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

Domain Skills

Good understanding of

• Banking domain (Cards, Deposit, Loans, Wealth management, & Insurance etc.)
• Audit Framework
• Data quality framework
• Risk & control Metrics

Soft Skills

• 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
• Should have 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
• Contribute to organizational initiatives in wide ranging areas including competency development, training, organizational building activities etc.
• Proactive approach in solving problems and eye for details
• A strong team player

Educational and Experience

• 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
• 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

Time Type: Full time

Citi is an equal opportunity employer, and qualified candidates will receive consideration without regard to their race, color, religion, sex, sexual orientation, gender identity, national origin, disability, status as a protected veteran, or any other characteristic protected by law.

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