About The Role:Trustworthy AI starts with trustworthy data. As CBRE builds AI agents across its People function, this role makes sure the data behind them, in one priority domain, is governed, well-defined and fit to rely on.
CBRE is running a significant People AI transformation to enable AI-powered experiences, automation and agentic workflows across the People function, starting with Talent Acquisition and People Services. This role represents People Data & Insights (PDI) within that program and keeps People data trusted, governed, documented and fit for purpose.
You serve as the designated Domain Data Steward for one of these priority domains. You coordinate and facilitate stewardship in partnership with the business Data Owners, who retain accountability for approving definitions and business rules, and you own the domain's semantic model: the entities, relationships and rules that describe its data. As the AI delivery teams and Digital and Technology (D&T) design the first agents, you embed in that design work and become the custodian of the semantic and access decisions they make, turning them into a durable, governed domain model that outlasts the design phase.
What You'll Do: Data stewardship and governance
- Serve as the designated Domain Data Steward for your domain, and facilitate stewardship across it while the business Data Owners keep sign-off on definitions and business rules.
- Partner with Data Owners, business stakeholders and Technology teams to promote effective stewardship of People data assets.
- Support enterprise data governance standards, policies and controls, and make sure data assets meet security and compliance requirements.
- Run stewardship activities through governance forums, working groups and stakeholder engagement.
Business definitions and semantic modeling
- Develop and maintain the domain's business glossary, Critical Data Element inventory and metadata documentation.
- Own the domain's semantic model, expressing its entities, relationships and business rules in the ontology and glossary, and keeping the logic used in reporting, analytics and AI traceable.
- Act as custodian of the semantic and access decisions made during the AI design work, capturing them and turning them into a durable, governed domain model.
- Specify the access and permission rules for the domain's data, and work to shared architecture principles so the domain model aligns with the other People domains rather than diverging.
AI and data readiness
- Make sure the data consumed by AI agents, automation and analytics products is governed, trusted and documented.
- Identify and manage AI-critical data assets, and help define the requirements for AI-approved datasets and certified business data products.
- Partner with AI delivery teams so the data used in AI solutions is appropriately governed and traceable, in support of responsible AI practice.
Data quality and lineage
- Support data quality monitoring and issue management, and coordinate the assessment and remediation of quality concerns that affect operations or AI.
- Maintain visibility of data lineage across source systems and downstream consumption layers, and work with Technology teams to keep lineage and metadata current.
Stakeholder partnership
- Represent People Data & Insights within strategic transformation initiatives.
- Build strong partnerships with HR leaders, Technology teams, governance functions and business stakeholders.
- Educate stakeholders on governance principles and stewardship responsibilities, and support adoption of data-driven decision-making and governance best practice.
Your domain
- You will steward one of the priority People domains and know its processes, data and platform in depth:
- Talent Acquisition: recruiting operations, requisitions, candidate lifecycle, sourcing and hiring, on Avature.
- People Services: HR service delivery, employee lifecycle transactions, case management and knowledge management, on ServiceNow.
- In either case: the definitions, rules and metrics that describe your domain, and the data it feeds to analytics, automation and AI.
What You'll Need:To perform this job successfully, an individual will need to perform each crucial duty satisfactorily. The requirements listed below are representative of the knowledge, skill, and/or ability required. Reasonable accommodations may be made to enable individuals with disabilities to perform essential functions.
Essential
- A bachelor's degree or equivalent practical experience.
- Experience in data governance, data stewardship or data management, including documenting business rules, data definitions and governance processes.
- A strong understanding of either Talent Acquisition or People Services processes and the data they generate, with hands-on experience of the relevant platform (Avature or ServiceNow), and the data modeling skill to express its entities, relationships and business rules in a semantic model or ontology, sufficient to challenge, validate and shape data definitions.
- Excellent written and verbal communication, with the stakeholder management to build productive relationships across business, functional and technical audiences and balance competing priorities with clarity and confidence.
- Comfortable working independently in a global, matrixed role across time zones, with the interpersonal skills, cultural awareness and energy to build relationships and momentum, and sensitivity to regional compliance, employment law and market-specific adoption.
- Organized and delivery-focused, with a track record of keeping complex, multi-workstream initiatives on track and escalating risks early and clearly.
- The ability to translate data into clear key performance indicators (KPIs) and insight, with a commercial focus on the decisions and value the data supports.
Desirable
- Familiarity with the DAMA-DMBOK data management framework and data governance best practice.
- Experience supporting AI, analytics or digital transformation initiatives, and familiarity with AI agent concepts, automation design or agentic workflow architecture, with a strong appetite to deepen this in a live delivery environment.
- Experience with metadata management, business glossaries and data lineage, and with cataloging and governance tools such as Collibra or Microsoft Purview.
- Data architecture experience, including Snowflake and medallion architecture, and exposure to ontology, semantic layer or knowledge-graph design.
You do not need every desirable item. If you meet the essentials and the role excites you, we want to hear from you.
