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.
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Job Type
Full-time
Career Level
Senior