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Role Overview

This Real Estate Finance Data Management, Analytics & AI Analyst Wipro role supports world’s largest alternative investment management company within the Real Estate Finance, working closely with global business, product and functional teams across the US, Europe and APAC. It combines hands-on data engineering and analytical capabilities with an understanding of finance to build trusted data foundations for valuations, performance, planning and reporting. The role offers exposure to real estate equity and debt, open- and closed-ended vehicles and multiple asset classes, while enabling scalable reporting, automation and frontier AI deployment.

Key Responsibilities

• Partner with Real Estate, Technology and Transformation teams to translate business needs into data requirements and practical technical solutions.
• Source, integrate and transform financial data; build and maintain warehouse models, tables and reusable datasets.
• Apply Python, SQL and data-modelling skills to support valuations, investment performance, FP&A, and management and investor reporting.
• Develop analytical and reporting solutions and apply industry-leading AI tools and frontier models to generate insights, streamline processes and automate finance workflows, with appropriate controls and validation.
• Stay current with developments in AI, machine learning, and data science, helping drive adoption of new capabilities across the RE Finance platform.
• Build data-quality checks, reconciliations and controls; document definitions, lineage and transformation logic.
• Coordinate cross-team testing, validation and implementation of data solutions, ensuring clear handovers, documentation and adoption.

Experience & Capabilities

• 1-3 years of relevant experience, depending on role level.
• Bachelor’s or master’s degree from a Tier-1 college or university in Engineering, Computer Science, Mathematics, Data Science, Operations Research, Statistics, Economics or a related quantitative discipline; finance training and certifications are an advantage.
• Hands-on experience working with complex financial datasets in Investment Banking, Asset Management, Private Markets, Fintech or another financial-services environment.
• Strong SQL, data-modelling and data-integration skills, with experience building and managing trusted datasets, warehouse models and data pipelines, ideally in Snowflake.
• Hands-on experience with Copilot, Cowork, Copilot Studio and frontier AI models to enhance data analytics, generate actionable insights, streamline processes and automate workflows.
• Working knowledge of financial statements, financial reporting and investment data; real estate or fund-finance experience is an advantage.
• Experience gathering and translating business requirements into scalable data solutions, reporting assets and technical specifications.
• Experience with data quality, reconciliation, controls, lineage, accessibility and documentation across complex financial datasets.
• Experience with analytical or visualisation tools such as Alteryx, Tableau, Power BI or Sigma, and an ability to build usable reporting solutions.
• Ability to explain technical concepts to business stakeholders, support delivery across business and technology teams, and identify opportunities for analytics, automation and future AI adoption.