About Circle K At Circle K, data is a strategic enterprise asset that powers growth, operational excellence, customer engagement, analytics, and AI innovation. As part of our Enterprise Data Governance organization, we are building modern governance capabilities that enable trusted data, certified data products, AI readiness, and scalable business value across a global enterprise.
We are seeking a
Lead Data Governance Analyst to drive governance, certification, adoption, and value realization across our modern data platforms, including Snowflake, Databricks, Informatica, and AI-enabled solutions. This role will play a critical part in advancing Data Products, Data Monetization, AI Governance, and trusted enterprise data capabilities.
Position Summary The Senior Data Governance & AI Enablement Lead is responsible for advancing Circle K's enterprise data governance strategy with a focus on:
- AI Governance and Enablement
- Data Platform Certification
- Metadata and Catalog Oversight
- Data Monetization Enablement
- Governance Adoption and Change Management
This role will partner closely with Data Product Managers, Business Product Managers, Data Stewards, Data Engineering, Analytics, Architecture, Security, Privacy, AI, and Business stakeholders to establish trusted, discoverable, reusable, and certified data assets that drive business outcomes and support responsible AI adoption.
A key responsibility will be leading governance and certification efforts across
Snowflake Horizon Catalog,
Databricks Unity Catalog, and
Informatica, ensuring business users and AI solutions have access to trusted and governed data products.
Success in this role will be measured through increased adoption of certified data products, improved data trust, accelerated data access, enhanced AI readiness, and measurable business value generated through governed data assets.
Key Responsibilities AI Governance & Enablement - Support the development and implementation of enterprise AI Data Governance frameworks, standards, and controls.
- Partner with AI, Analytics, and Data Science teams to ensure AI solutions utilize trusted and governed data assets.
- Support AI governance reviews, risk assessments, and approval processes.
- Establish metadata, lineage, and data quality requirements that improve AI readiness.
- Drive responsible AI practices aligned with regulatory, privacy, and governance requirements.
Data Products & Data Monetization - Support the development, certification, and governance of enterprise Data Products across Customer, Item, Site, Vendor, Finance, Loyalty, Fuel, HR, and Digital domains.
- Partner with Data Product Managers and business stakeholders to define governance requirements and success criteria for data products.
- Enable Data Monetization opportunities by ensuring data assets are discoverable, trusted, reusable, and scalable.
- Support measurement of Data Product adoption, usage, business value, and operational effectiveness.
- Identify opportunities to leverage data as a strategic asset to improve revenue, reduce costs, enhance customer experiences, and support AI innovation.
- Develop governance processes that accelerate self-service analytics and data product consumption while maintaining appropriate controls.
Data Platform Certification - Establish and manage enterprise certification processes for datasets and data products.
- Drive adoption of trusted and certified assets across Snowflake and Databricks.
- Define certification standards including:
- Maintain certification workflows, scorecards, and reporting.
Metadata & Catalog Governance - Manage business and technical metadata standards across:
- Snowflake Horizon Catalog
- Support implementation of the Enterprise "Catalog of Catalogs" strategy.
- Drive business glossary development and stewardship.
- Improve data discoverability through metadata enrichment and governance automation.
- Support synchronization of metadata, classifications, glossary terms, lineage, and governance information across platforms.
Data Quality & Governance Operations - Partner with business and technical teams to identify Critical Data Elements (CDEs).
- Support enterprise data quality monitoring, scorecards, issue management, and remediation processes.
- Assist with implementation of AI-assisted data quality monitoring and governance automation capabilities.
- Develop governance metrics and executive reporting.
Governance Adoption & Change Management - Lead governance enablement, training, and awareness programs.
- Support Data Owners, Data Stewards, Data Product Owners, and Data Custodians in executing governance responsibilities.
- Develop communications, training materials, job aids, and governance documentation.
- Promote adoption of certified datasets, trusted data products, and governance best practices across the enterprise.
Required Qualifications - 7+ years of experience in Data Governance, Data Management, Data Quality, Metadata Management, Data Products, or related disciplines.
- Experience supporting enterprise governance programs and governance operating models.
- Experience working with modern cloud platforms including:
- Understanding of AI readiness, responsible AI practices, and governance frameworks.
- Experience driving adoption, change management, and stakeholder engagement initiatives.
- Strong communication and executive presentation skills.
- Experience working in Agile delivery environments.
Preferred Qualifications - Experience with Informatica IDMC, Data Catalog, Data Quality, MDM, or Governance solutions.
- Experience with Snowflake Horizon Catalog and Databricks Unity Catalog.
- Experience implementing data certification and trusted data product programs.
- Experience supporting Data Product operating models and Data Mesh concepts.
- Familiarity with GDPR, CCPA, SOX, PCI, and other regulatory frameworks.
- Experience supporting Data Monetization, customer analytics, digital products, or advanced analytics initiatives.
- CDMP certification or similar industry certification preferred.
- MBA or advanced degree in Information Systems, Computer Science, Data Analytics, Business, or related field preferred.
Success Measures Success in this role will be measured by:
- Increased adoption of Circle K Master Data via Informatica MDM.
- Increased adoption and consumption of certified Data Products.
- Growth in certified datasets and trusted data assets across Snowflake and Databricks.
- Improved metadata completeness, quality, and lineage coverage.
- Reduced time required to discover, access, and utilize trusted data.
- Increased business value generated through governed Data Products.
- Enhanced AI readiness and governance compliance.
- Increased participation from Data Owners, Data Stewards, and Data Product Owners.
- Demonstrated support of Data Monetization opportunities through improved accessibility, quality, and governance of enterprise data assets.
- Improved governance maturity, operational efficiency, and user satisfaction.
Why Join Circle K? This is an opportunity to shape the future of Data Governance, AI Data Enablement, and Data Products at a global organization undergoing significant digital transformation. You will help establish trusted data foundations, enable responsible AI adoption, drive Data Product success, and unlock business value through governed and monetized data assets.
Better Data. Trusted AI. Governed Data Products. Greater Business Value. Circle K is an Equal Opportunity Employer.
The Company complies with the Americans with Disabilities Act (the ADA) and all state and local disability laws. Applicants with disabilities may be entitled to a reasonable accommodation under the terms of the ADA and certain state or local laws as long as it does not impose an undue hardship on the Company. Please inform the Company's Human Resources Representative if you need assistance completing any forms or to otherwise participate in the application process.Click below to review information about our company's use of the federal E-Verify program to check work eligibility:
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