Senior Manager, Data Governance

Investment Management Corporation of Ontario (IMCO)•Toronto, ON

1d•Hybrid

About The Position

The Senior Manager, Data Governance is a key enterprise role accountable for defining, standing up, and operationalizing IMCO’s enterprise data governance framework. This role balances strong leadership with hands‑on execution, ensuring data is consistently defined, trusted, and fit for purpose across investments, analytics, reporting, data products, and AI use cases. Reporting to the Director, Data Enablement, the role serves as IMCO’s enterprise authority on data governance, with influence at senior leadership forums. The mandate goes beyond policy definition, this role actively partners with business, operations, and technology leaders to translate the approved data strategy into practical standards, scaled capabilities, and embedded execution across initiatives. Success requires bringing real‑world delivery experience to help teams implement governance in day‑to‑day decision‑making, not as a parallel process.

Requirements

10+ years of progressive experience in data governance, data management, or enterprise data roles within asset management, wealth management, pension funds, capital markets, or similarly regulated financial services environments.
Proven track record designing, scaling, or maturing enterprise data governance programs, including standards, councils, stewardship models, and operating frameworks.
Demonstrated success operating at leadership level, influencing senior business, investment, and technology leaders without direct authority.
Experience embedding governance into data platforms, analytics delivery, and data product operating models, rather than operating as a standalone compliance function.
Hands‑on experience with enterprise data governance and data management tooling, such as data catalogs, business glossaries, lineage, metadata management, and data quality platforms.
Enterprise mindset: able to balance business value, risk, and scalability.
Strong stakeholder leadership facilitates consensus across investment, finance, risk, legal, and technology teams.
Data modeling literacy: conceptual and logical data models, metamodels, and their relationship to physical data assets.
Data product and AI awareness: understands how governance enables reuse, automation, advanced analytics, and AI safely.
Comfort in regulated environments: audit‑ready, evidence‑based, and disciplined without being bureaucratic.
Change leadership: drives adoption through councils, tooling, standards, and practical enablement.

Nice To Haves

CDMP (Certified Data Management Professional) or equivalent data management / governance certification.
Familiarity with DAMA‑DMBOK principles and modern enterprise data governance practices
Familiarity with AI governance or responsible AI frameworks.

Responsibilities

Define and operationalize IMCO’s enterprise data governance framework, balancing leadership with hands‑on execution to ensure governance is embedded into day‑to‑day delivery across the organization.
Serve as IMCO’s enterprise authority on data governance, influencing senior leadership forums and partnering with business, operations, risk, and technology leaders to translate strategy into practical, scalable execution.
Establish and enforce enterprise data standards and decision rights, including data definitions, critical data elements, ownership, stewardship, lineage, and quality, to drive consistency, trust, and accountability.
Stand up and mature core data management capabilities and tooling (metadata, data quality, lineage, issue management, cataloging), ensuring strong adoption and integration into delivery rather than parallel processes.
Embed governance by design into initiatives, data products, and AI use cases, ensuring quality, controls, lineage, and accountability are implemented upfront to enable reuse and reduce downstream remediation.
Support the evolution of AI governance practices, including alignment with enterprise risk, compliance, and responsible AI principles, leveraging strong data foundations to enable safe and scalable AI adoption.
Operationalize data ownership and stewardship within business teams, providing hands‑on guidance and support to ensure accountability for data quality, metadata, and issue resolution.
Provide executive assurance on governance adoption and data health, partnering with Risk and Compliance to surface material data risks, maturity, and remediation progress in a clear, decision‑ready manner.