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Senior Data Governance Analyst

tera · Toronto · Canada · On-site

Pay: CAD 110,000 – 132,000 a year

Posted Aug 25, 2026

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Senior Data Governance Analyst Who We Are Teranet is Canada’s leader in the delivery and transformation of statutory registry services with extensive expertise in land and commercial registries. We also market insightful property and data solutions, as well as practice management automation to thousands of customers in real estate, financial services, government, utilities, and legal markets. Connect. Grow. Thrive Together. To learn more about who we are visit our website:  www.teranet.ca About the Role The Senior Data Governance Analyst supports Teranet’s Data and AI Governance and Management Program by helping ensure enterprise data is trusted, protected, responsibly used, and effectively managed throughout its lifecycle. Working with business, technology, Information Security, Privacy, Data Analytics, Data Management, Data Architecture, and AI stakeholders, this role helps mature governance policies, standards, controls, risk practices, metadata, data catalogs, DSPM, retention, and AI Governance capabilities. Guided by Teranet’s governance strategy, the role helps implement new technology-enabled governance capabilities and build the practical processes, workflows, automation, and controls needed to operationalize them across tools, platforms, and business teams. It supports alignment with recognized frameworks such as DAMA-DMBOK, DCAM, ISO/IEC 38505, ISO/IEC 27001, NIST AI RMF, and ISO/IEC 42001, while enabling analytics, reporting, data lake expansion, data architecture, continuous compliance, and Governed AI use cases. What You’ll Be Doing   Governance Program and Operating Model Support the operation and maturation of Teranet’s Data and AI Governance Program, including governance forums, initiative planning, metrics, issue tracking, and program reporting. Develop, review, and operationalize governance policies, standards, controls, procedures, and stewardship practices. Translate policy, risk, data management, and business requirements into practical workflows, controls, and operating procedures that simplify governance adoption and embed requirements into day-to-day ways of working. Metadata , Catalog , and Data Enablement Maintain and improve metadata repositories, business glossaries, data catalogs, lineage, classification, tagging, and sensitivity labeling across structured and unstructured data environments. Partner with Data Management, Data Architecture, Data Analytics, and technical teams to embed governance requirements into data products, reporting assets, data models, platform designs, and enterprise data standards. Support initiatives that improve the quality, usability, structure, and governance of data used for analytics, reporting, data lake expansion, architecture, and AI-enabled use cases. Risk, Compliance, Retention, DSPM, and AI Governance Develop and monitor data quality metrics, identify issues, and support remediation with business and technical stakeholders. …