VP Global Workforce Optimization Data Architecture Lead Analyst

About Citi

Citi, the world leading global bank, has approximately 200 million customer accounts and a presence in more than 160 countries and jurisdictions worldwide. Citi provides consumers, corporations, governments, and institutions with a broad range of financial products and services, including consumer banking and credit, corporate and investment banking, securities brokerage, transaction services, and wealth management. Citi enables clients to achieve their strategic financial objectives by providing them with cutting‑edge ideas, best‑in‑class products and solutions, and unparalleled access to capital and liquidity.

A critical enabler of Citi’s mission to enable growth and economic progress is technology. Our teams are creating innovations used across the globe – we’re changing the way people bank and how the world does business.

Please note that we are unable to offer visa sponsorship for this position. All applicants must be legally authorized to work in United States without the need for company sponsorship, now or in the future.

Citi’s Global Workforce Optimization (GWFO) is an organization within Citi’s Chief Operating Office and Enterprise Operations. Our organization designs solutions providing transparency & visibility of the current state; and functions to leverage enterprise solutions to drive improved process & workforce optimization; and supports the evolution of the organization via continuous improvement & simplification.

Our GWFO mission is to partner with Citi businesses globally to improve customer experience, increase revenue, achieve service objectives, and maximize efficiency. GWFO support includes workforce management related activities, including capacity planning, analytics, and supplier tools support. Across the Citi Enterprise, we strive to:

• Drive workforce strategy and provide insights across capacity planning and supported applications to optimize people and processes
• Enable discipline, create consistency, and vigorously improve processes
• Deliver & optimize applications and tools in real-time while driving control rigor
• Serve as a trusted partner and subject matter expert supporting key strategic work

The Global Workforce Optimization (GWFO) Data Architecture Senior Analyst is a seasoned, data‑savvy specialist who serves as the in‑house data Subject Matter Expert (SME). In this role, you will partner directly with internal “clients” to translate data needs into scalable data pipelines, integrations, governance‑aligned datasets, and repeatable onboarding patterns. You will lead and deliver high‑impact data initiatives that improve data maturity, simplify data onboarding, and accelerate “speed‑to‑market” data outcomes.

The ideal candidate should possess a strong technical data foundation, comfortable with ambiguity with thinking outside the box mentality and have a passion for problem solving complex data needs into strategic solutions. This function covers incumbents responsible for various data activities, which include subject matter expertise in the latest data concepts, database architecture / design engineering, and ability to translate highly complex data technical specifications from clients into well designed data integration outcomes.

• Partner with internal clients to capture data needs, define onboarding approach, and integrate data into the GWFO product suite
• Own end‑to‑end data onboarding delivery: intake, requirements, mapping, integration design, build, validation, and release
• Establish repeatable onboarding data playbooks and templates that simplify GWFO data maturity and reduce time‑to‑value.
• Manage relationships with key stakeholders across the organization, including the day‑to‑day execution of activities and meetings
• Leads larger projects with broader impact. Interacts and onboard new clients, partners with existing clients, and focused on integrating client data into our product suite for workforce solutions
• Liaises with multiple data teams/departments, technology partners, and serves as subject matter for planning and analysis of project deliverables and processes for data initiatives