Assistant Vice President - Data Analytics
Citi · India · 7d ago
About Us
With Citi’s Analytics & Information Management (AIM) group, you will do meaningful work from Day 1. Our collaborative and respectful culture lets people grow and make a difference in one of the world’s leading Financial Services Organizations. The purpose of the group is to enable building Citi’s data assets, analyze information, and create actionable intelligence for our business leaders.
The Wealth Data Strategy team partners across Business, Technology, Data, Governance, and Analytics to create scalable data solutions. We work on large-scale data transformation initiatives that bring together fragmented data across regions, businesses, and source systems into trusted, consumption-ready data foundations for the Wealth organization.
Position
We are hiring an Assistant Vice President (C12) – Data Management/Information Sr Analyst to join the Wealth Data Strategy team.
This is an exciting opportunity to play a dual Product Owner / Business Analyst role in One Wealth, Citi Wealth’s premier strategic data transformation program. You will help shape how Wealth data is sourced, modeled, governed, validated, and consumed across the global organization.
The role requires a strong mix of business acumen, data knowledge, stakeholder management, and Agile execution. You will work closely with business stakeholders, technology teams, data modelers, governance partners, and downstream consumers to translate business needs into high-quality, governed data products.
Key Responsibilities
- Product Ownership & Data Product Delivery: Own and drive data product requirements from discovery to delivery. Define scope, prioritize requirements, manage backlog, track delivery and ensure the final output meets business and consumption needs.
- Business Analysis & Requirement Management: Partner with business stakeholders to understand objectives, reporting needs, metrics, operational processes and pain points. Translate business requirements into clear functional, data and technical requirements.
- Hands-on Data Analysis: Use SQL, Python or similar tools to analyze datasets, validate source data, perform data profiling, investigate issues, create metrics and support business/data analysis.
- Source Data Discovery & Mapping: Work with source-system owners, technology teams and domain teams to identify required datasets, attributes, business definitions, lineage, refresh frequency, source availability and data gaps.
- Source-to-Target Mapping: Support detailed mapping of source attributes to target data models. Work with Tech BAs, data modellers and engineering teams to clarify mapping logic, transformation rules, derivations and dependencies.
- Data Model & Data Dictionary Review: Review logical models, physical models, data dictionaries and DDLs. Ensure the model supports agreed business metrics, reporting needs, analytics use cases and cross-domain consumption.
- Metrics & Reporting Enablement: Define and validate business metrics, KPIs and data requirements for dashboards, reports and analytics use cases. Partner with BI/reporting teams to ensure data is fit for consumption.
- Data Quality & Production Validation: Define validation approach, data reconciliation checks, completeness checks, DQ rules, test scenarios, PAT/UAT support and production validation. Investigate data quality issues and drive closure with technology/domain teams.
- Data Governance & Controls: Support data classification, sensitivity review, cross-border considerations, access controls, governance approvals and data ownership processes for data movement and consumption.
- AI & Automation Enablement: Identify opportunities to use AI and automation for data discovery, mapping, data quality rule creation, SQL generation, production monitoring, documentation and knowledge management.
- Stakeholder Management: Act as a trusted bridge between Business, Technology, Data Modelling, Governance, source-system teams and downstream consumers. Drive meetings, follow-ups, issue resolution and clear communication across global teams.
- Documentation & Executive Communication: Create and maintain clear documentation including requirements, user stories, data mappings, business definitions, data gaps, status updates, issue logs, executive summaries and presentation materials.
- Mentorship & Collaboration: Support junior team members by sharing domain, data and delivery knowledge. Promote ownership, collaboration, continuous improvement and strong delivery discipline within the team.
Key Qualifications
- Education: Bachelor’s degree in computer science, Information Technology, Business Administration, Data Analytics, Engineering, Finance or a related field.
- Experience: Minimum 7-8+ years of experience in Data Management, Business Analysis, Product Ownership, Data Strategy, Analytics, Business Intelligence, Data Governance or related roles. Prior experience in Banking, Wealth Management or Financial Services is preferred.
- Product Owner / Business Analyst Experience: Strong experience working as a Product Owner, Business Analyst, Data Analyst or Data Product Lead, including requirement gathering, backlog management, stakeholder engagement, delivery tracking and business sign-off.
- Strong SQL Skills: Hands-on experience writing SQL queries for data analysis, profiling, reconciliation, metric creation, validation and issue investigation.
- Python / Analytical Programming: Working knowledge of Python or similar programming/scripting tools for data analysis, automation, validation or reporting support.
- Data Platform Knowledge: Good understanding of data warehouses, data lakes, ETL/ELT pipelines, metadata, lineage, source-to-target mapping, data models and data quality concepts. Experience with platforms such as Snowflake, Hadoop/Hive, Teradata or similar technologies is preferred.
- BI & Reporting Knowledge: Hands-on experience or strong working knowledge of BI/reporting tools such as Tableau, Power BI, Qlik, Dataiku or similar platforms. Ability to understand dashboard requirements, metrics and reporting consumption needs.
- Data Governance & Quality Awareness: Understanding of data classification, sensitive data handling, access controls, regulatory considerations, data quality controls, reconciliations and production validation processes.
- AI / Automation Awareness: Knowledge of AI use cases in data management, analytics, automation, data quality, reporting or knowledge management. Practical exposure to AI-assisted SQL generation, documentation, rule creation or automation is an advantage.
- Communication & Stakeholder Management: Strong communication skills with the ability to explain business, data and technology concepts clearly. Ability to work with senior stakeholders across business, technology and governance teams.
- Problem Solving: Strong analytical mindset with the ability to work through ambiguity, investigate data issues, connect dots across teams and drive closure.
- Leadership & Collaboration: Ability to work independently, influence without direct authority, mentor junior team members and collaborate effectively across global teams.
Preferred Skills
- Domain knowledge in Wealth Management (Client/Account data, Investments, Deposits, Lending, or Financial Products).
- Experience working on enterprise data lakes, data warehouses, or Unified Data Models (UDMs).
- Familiarity with data cataloging, data quality tools, and metadata management workflows.
- Exposure to AI-assisted data management, automated rule generation, or knowledge management solutions.
Additional Information
This role provides an opportunity to work on a strategic Wealth data transformation initiative, partnering with global business and technology teams to build trusted, governed and reusable data products.
The successful candidate will play a key role in shaping how Wealth data is sourced, modelled, validated and consumed across Citi, while building deep expertise across business, data, technology and governance. This is a strong opportunity for someone who enjoys solving complex data problems, working with senior stakeholders and contributing to high-impact data transformation work.
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Job Family Group:
Decision Management------------------------------------------------------
Job Family:
Data/Information Management------------------------------------------------------
Time Type:
Full time------------------------------------------------------
Most Relevant Skills
Please see the requirements listed above.------------------------------------------------------
Other Relevant Skills
For complementary skills, please see above and/or contact the recruiter.------------------------------------------------------
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