Director, Enterprise Data Governance

About QuadReal Property Group QuadReal Property Group is a global real estate investment, development and operating company headquartered in Vancouver, British Columbia. Its assets under management are $98.5 billion. From its foundation in Canada as a full-service real estate operating company, QuadReal has expanded its capabilities globally for investments in equity and debt in both the public and private markets. QuadReal invests directly through operating platforms in which it holds an ownership interest and via programmatic partnerships. QuadReal seeks to deliver strong investment returns while creating sustainable environments that bring value to the people and communities it serves. Now and for generations to come. QuadReal: Excellence lives here. www.quadreal.com Role Description

The Director, Enterprise Data Governance is accountable for defining and governing the enterprise data QuadReal relies on, anchored in DAMA-DMBOK, covering data definitions, ownership, quality, and observability. This makes QuadReal's data reliable enough to be governed, measured, and controlled, reducing the risk that decisions, reporting, and controls rest on data that can't be trusted. The role reports to the VP, Risk & Integrated Assurance and turns the VP's enterprise-wide mandate into one accountable operating model focused on risk mitigation through data governance lens. Success is measured by the risk it mitigates: data issues caught before they become decisions made on incorrect information, ownership gaps closed before they become accountability gaps. Holding up under audit is one key aspect of that risk mitigation but not the goal in itself. The Director also supports the VP's overall view of QuadReal's risk and control environment and represents Data Governance in Risk & Integrated Assurance reporting.

Key Responsibilities

Enterprise Data Governance Define QuadReal’s enterprise data definitions, classifications, and Critical Data Elements (CDEs), anchored in DAMA-DMBOK. Own the data ownership and accountability model: name Data Owners, Stewards, and Custodians, and hold them accountable through a defined sign-off cadence. Deliver the enterprise business glossary under a tiered governance model, and maintain metadata management, lineage standards, and dbt metadata synchronization across the platform. Set data quality thresholds and Trusted Layer certification criteria, and hold data observability (freshness, pipeline health, trust scores) to the same standard as financial controls. Align controls as gates across the data delivery lifecycle (ingestion, definition, build, use, and govern), so a control fires wherever data advances and nothing reaches a certified output without passing. Build data governance capability across the business through training and playbooks, rather than keeping expertise centralized. Integration and Decision Authority Act as the link between Business Controls and Data Governance called for in the integrated operating model: define control standards and evidence expectations alongside data definitions, and build controls into new systems and initiatives from the start. Where control standards and data definitions conflict, collaborate with relevant stakeholders including ED&A, Business Owners and Business Controls to resolve these inconsistencies. Work with ED&A / Technology and the Data Platform team so controls and governance are proactively built into the toolchain (Microsoft Fabric, dbt, Airflow, Power BI, Purview, Entra ID, Quadrant) by design. Represent Data Governance in Risk & Integrated Assurance meetings and support Audit Committee reporting. Team Leadership Lead and develop direct report(s) and set clear deliverables and cadence for them. Build team capability in data analytics, AI literacy, and integrated systems controls as the role grows, and build bench strength to move the environment from project to sustained run-state without single points of failure. Build a “one team” culture between Business Controls and Data Governance that removes duplicate work and closes the gaps that used to sit between the two groups. What Success Looks Like Controls operating as gates, each with a named owner and re-performable evidence. Audit outcomes: clean walkthroughs, deficiencies remediated, and SOC scope defensible. Glossary and standards adopted, so certified numbers are built on agreed definitions. Governance measured by delivery: trusted, in-use data products standing behind reported figures. Direct reports delivering to plan, with growing capability and bench strength. Qualifications

Bachelor’s degree in Accounting, Finance, Business, Risk Management, Data Management, Computer Science, or a related discipline; Master is an asset. 8+ years of progressive experience across data governance, risk management, or audit, including at least 2 years leading people, and demonstrable end-to-end delivery of a control or governance environment. Working knowledge of ICFR,