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Enterprise Data Product Lead

Job in New York, New York County, New York, 10261, USA
Listing for: CBRE
Full Time position
Listed on 2026-07-02
Job specializations:
  • IT/Tech
    Data Engineering, Business Intelligence, Data Warehousing, Business Systems/ Tech Analyst
Salary/Wage Range or Industry Benchmark: 200000 - 250000 USD Yearly USD 200000.00 250000.00 YEAR
Job Description & How to Apply Below
Location: New York

About the Role

As a CBRE Enterprise Data Product Lead, you will own and drive the full lifecycle of enterprise data products from strategy through scaled adoption to enable data‑driven decision‑making across the organization. You will serve as the connective tissue between technical data teams and business stakeholders, translating complex data capabilities into scalable, high‑value products across segments and corporate functions including Investment, Leasing, Operations, and Finance.

This job is part of the Data Science & Analytics job function. You will be responsible for defining and delivering data products that improve organizational effectiveness, enable self‑service analytics, and support predictive and prescriptive business intelligence at scale leveraging modern platforms including cloud data warehouses, AI tooling, and enterprise governance frameworks.

What You’ll Do
  • Define and own the enterprise data product vision, strategy, and roadmap in alignment with business priorities.
  • Lead cross‑functional collaboration with data, engineering and business stakeholders to deliver high‑quality, reliable data products at enterprise scale.
  • Apply in‑depth knowledge of modern data platforms including Snowflake, Reltio, cloud platforms, data governance tooling (Collibra, Alation), and BI tools (Power BI, Tableau) to guide architectural and technology decisions.
  • Champion a data‑as‑a‑product mindset across the organization, driving cultural and operational change to treat data with the same rigor as software products.
  • Act as the primary product owner for enterprise data assets, managing the full product lifecycle from discovery and design through delivery, adoption, and iteration across complex, multi‑platform, fragmented environments.
  • Establish and enforce data product standards, including data contracts, SLAs, data quality frameworks, and publication practices.
  • Accelerate time‑to‑market for data products using AI (e.g., Cursor, Claude Code, Microsoft Copilot) to accelerate delivery.
  • Lead build‑out of high‑impact data products to deliver measurable business value.
  • Oversee the development of self‑service data platforms to democratize access to trusted data across business units.
  • Lead cloud‑based Master Data Management design and implementation, including integration with enterprise systems like CRM (Salesforce), Financial systems.
  • Partner with data governance teams to ensure enterprise data products meet compliance, privacy, and security requirements.
  • Define and monitor key performance indicators (KPIs) for data product adoption, quality, and business impact.
  • Direct the resolution of complex data product challenges like data quality, integration and adoption barriers through advanced critical thinking.
  • Lead and mentor a team of data product managers, providing guidance on prioritization, stakeholder engagement, and delivery execution.
  • Negotiate with senior business and function leads to reach agreement on data product strategy, investment, and priorities.
  • Lead by example and model behaviors consistent with CBRE RISE values.
What You’ll Need
  • Bachelor’s Degree preferred (e.g., Engineering or Technology) with 15 years of relevant experience in data management, analytics, or technology product management. In lieu of a degree, a combination of experience and education will be considered.
  • Demonstrated experience establishing and scaling enterprise data products from the ground up, including prioritization, design, development, launch, and support.
  • Proven track record delivering measurable business value through data products across large, complex enterprises.
  • Cross‑sector experience is strongly preferred.
  • Deep hands‑on experience with modern data stack technologies: cloud data warehouses and lakes (Snowflake, Azure, AWS), cloud data integration tools, and BI/analytics tools (Power BI, Tableau).
  • Experience with AI/GenAI tools and platforms (e.g., Claude, Cursor, Microsoft Copilot) to accelerate data product delivery and enable intelligent analytics.
  • Proficiency with data governance and MDM platforms (Collibra, Reltio) and familiarity with regulatory compliance requirements in enterprise data contexts.
  • Experience working across…
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