Manager, Data Governance

Benevity•Toronto, ON

2d•CA$131,800 - CA$172,480•Hybrid

About The Position

Benevity is the way the world does good, providing companies (and their employees) with technology to take social action on the issues they care about. Through giving, volunteering, grantmaking, employee resource groups and micro-actions, we help most of the Fortune 100 brands build better cultures and use their power for good. We’re also one of the first B Corporations in Canada, meaning we’re as committed to purpose as we are to profits. We have people working all over the world, including Canada, Spain, Switzerland, the United Kingdom, the United States and more! Benevity's software architecture has evolved to include a diverse technology stack. The front end application, using mainly VueJS, is designed for both desktop and mobile web rendering. Our back end systems (some Java SpringBoot, some PHP) manage data processing, interfaces with external providers, and ensures robust security. We run and operate our systems in AWS and GCP cloud, leveraging where possible cloud native technology. We emphasize clean, maintainable code and use GIT for version control and collaboration. Additionally, our platform integrates with various external services for functionalities like email communication, content storage, and server to server interactions. Our culture is driven by our core value of "we are we" and as a Manager of Data Governance you will work in an outcome driven environment where collaboration with your product, design and engineering counterparts is paramount. If you are eager to make a difference and thrive in a collaborative setting, we invite you to join our team! Data Governance exists so that the rest of the organization can trust what they are working with. The Manager of Data Governance sets the rules, owns the standards, and holds everyone accountable. This role is the organizational authority on what data exists, who owns it, where it came from, and who can access it. On quality specifically, this team defines what good looks like. Engineering and DataOps make it happen. Governance checks whether it actually did. The ideal candidate is a confident cross functional leader who can build programs, influence without authority, and translate policy into practice across a complex data organization.

Requirements

Degree in Computer Science, Information Management, Business, or equivalent professional experience.
7 or more years of experience in data governance, data management, or a closely related field, with at least 2 years in a people or program leadership role.
Hands on experience operating a data catalog or metadata management platform. Experience with DataHub is strongly preferred. Familiarity with Collibra, Alation, or Atlan is a significant asset.
Working knowledge of data observability and quality tooling, including platforms such as Monte Carlo, Lightup, Great Expectations, or dbt.
Familiarity with privacy and entitlement governance platforms such as OneTrust, Privacera, or equivalent.
Strong understanding of data quality frameworks, including how to define dimensions, set SLAs, build health scores, and drive remediation.
Experience designing and enforcing data classification schemes and access governance frameworks in a cloud environment (AWS, Azure, or GCP).
Solid understanding of regulatory and compliance requirements relevant to data, including GDPR, CCPA, SOC 2, and internal audit standards.
Demonstrated ability to facilitate cross functional councils or governance bodies, drive alignment among opinionated stakeholders, and hold teams accountable to standards.
Strong communication skills. You can write a policy, present findings to an executive audience, and translate data governance concepts into language that non technical stakeholders act on.
Experience working with dbt and understanding how lineage, documentation, and testing practices connect to governance outcomes.
Ability to build programs from the ground up and operate in an environment where governance practices are still maturing.

Nice To Haves

DAMA Certified Data Management Professional (CDMP) certification
Experience with DataHub Cloud or Acryl Data
Familiarity with Apache Atlas or AWS Glue Data Catalog
Experience building data governance programs in a SaaS or B2B technology company
Exposure to MLOps governance or AI model risk frameworks

Responsibilities

Lead and grow the Data Governance function, setting the strategic direction for data ownership, stewardship policy, access governance, and data classification standards across the organization.
Own and operate DataHub as the living catalog of the organization's data assets, covering metadata management, catalog onboarding, tagging, lineage registration, and domain stewardship.
Extend the governance toolchain beyond DataHub by evaluating and deploying complementary platforms such as Collibra, Alation, or Atlan for policy management and business glossary; Monte Carlo or Lightup for data observability; OneTrust or Privacera for privacy and entitlement governance; and Great Expectations or dbt tests for quality rule enforcement.
Own the enterprise Data Quality Framework, defining six quality dimensions that apply across all functions: Completeness, Accuracy, Timeliness, Consistency, Validity, and Uniqueness.
Classify every data asset into a quality tier: Tier 1 for business critical, Tier 2 for operational, Tier 3 for exploratory. SLAs and enforcement standards are documented, visible, and enforced by tier.
Formally document data quality SLAs per domain and per tier, publish them in DataHub, and review them on a biannual cadence.
Define and publish a data health score methodology. Domain health scores are visible in the catalog and reported monthly to the data domain council.
Conduct quarterly data quality audits across all functions, share findings with the domain council, and assign remediation with named accountability and due dates.
Define and maintain the profiling policy: which datasets are profiled, how often, and what thresholds trigger an escalation. This is never left to individual interpretation.
Govern the separation between defining quality rules and implementing them. Governance defines. Engineering and DataOps implement. When a breach occurs, Governance escalates to the owning function and tracks resolution.
Own access control and entitlements governance, ensuring data sensitivity classifications are applied and access is granted and revoked in accordance with policy.
Lead compliance alignment across privacy regulations, internal audit requirements, and industry standards. Partner with Legal and Security to ensure data handling practices are always current.
Facilitate the cross functional data domain council, driving alignment across data owners, stewards, and platform teams on standards, escalations, and roadmap priorities.
Build a culture of data accountability across the organization through training, communication, and stakeholder engagement programs.