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About the Role:

The Entry-Level Global Corporate Real Estate Portfolio Data Analyst supports the global Corporate Real Estate (CRE) team in managing the occupied portfolio (leased and owned properties) by maintaining high-quality data, producing KPIs and global reports, and analyzing information to support decision-making. This role focuses on working with datasets covering leases, locations, area, headcount, and real estate costs, ensuring that information is complete, consistent, and available in a standard format across the organization.

Key Responsibilities  

• Maintain accurate, structured data on lease contracts, locations, area, headcount, and real estate costs in core CRE systems (lease administration / IWMS / portfolio tools).
• Develop and update recurring portfolio reports and dashboards (e.g., headcount vs. capacity, occupancy and utilization, rent roll, lease expirations, space per person, costs per square meter and per person) for different regions and organizational levels.
• Collect and produce global office space utilization reports, consolidating information from different tools, regions, and data sources.
• Perform portfolio data analyses to support decisions on site openings, closures, expansions, consolidations, or space reconfigurations (e.g., scenario comparisons, cost impacts, efficiency metrics)
• Analyze and configure data from non-conforming data sets (non-standardized or differently structured sources) to report the portfolio in a standardized and comparable format at a global level.
• Support data loading, validation, and cleansing activities during new system implementations, process changes, or data migrations.
• Collaborate with regional and local teams to clarify data questions, resolve discrepancies, and complete missing information.
• Create visualizations, charts, and executive presentations to communicate key findings to non-technical stakeholders.
• Document data definitions, business rules, update processes, and portfolio data sources.
• Provide ad hoc analytical support for CRE projects (new sites, consolidation initiatives, workplace pilots, surplus space and sublease analysis), as well as any other portfolio analysis requested by internal clients.

Qualifications  

• Bachelor’s degree in Engineering, Finance, Economics, Actuarial Science, Mathematics, Business Administration, Data Analytics, Information Systems, Architecture, or related fields.
• Advanced English (ability to read, document, and communicate with global teams).
• 2 years of prior experience in data analysis, finance, planning, BI, consulting, corporate real estate, or similar functions (relevant internships and co-op experience are acceptable).
• Intermediate to advanced Excel skills (pivot tables, formulas, handling large datasets).
• Preferred experience with data visualization tools (e.g., Power BI, Tableau, Qlik, Looker, or similar)
• Preferred basic experience with databases (e.g., SQL) or data analysis tools.

Competencies and Skills  

• High attention to detail and accuracy in data management.
• Analytical thinking and structured problem-solving.
• Strong data stewardship mindset and sense of ownership over data quality.
• Curiosity about how workplace, location, and cost decisions support the company’s business strategy and employees.
• Ability to manage multiple requests and deadlines in a large, global, matrixed organization.

Why CBRE?

When you join CBRE, you become part of the global leader in commercial real estate services and investment that helps businesses and people thrive. We are dynamic problem solvers and forward-thinking professionals who create significant impact. Our collaborative culture is built on our shared values — respect, integrity, service and excellence — and we value the diverse perspectives, backgrounds and skillsets of our people. At CBRE, you have the opportunity to chart your own course and realize your potential. We welcome all applicants.

Applicant AI Use Disclosure

We value human interaction to understand each candidate's unique experience, skills and aspirations. We do not use artificial intelligence (AI) tools to make hiring decisions, and we ask that candidates disclose any use of AI in the application and interview process.