Accountabilities

• Drive data governance, quality, and integrity initiatives across critical relationship data domains, ensuring data assets remain trusted, consistent, accurate, and fit for purpose.
• Govern Ownership, Individuals, and Sanctions data by defining and maintaining data standards, business rules, critical data elements, metadata, and data quality controls.
• Partner with business and technology stakeholders to establish data requirements, definitions, ownership responsibilities, stewardship models, and accountability frameworks.
• Develop and implement data quality controls, metrics, monitoring processes, root-cause analysis, and remediation programs to address data quality issues.
• Create and maintain governance artifacts, including business glossaries, metadata, data definitions, governance documentation, and related standards.
• Support master data and reference data management practices to improve consistency, integrity, accessibility, and usability across enterprise data assets.
• Track governance issues, risks, actions, and remediation activities, ensuring appropriate follow-up, escalation, and timely resolution.
• Facilitate data governance forums and influence stakeholders to strengthen data accountability, stewardship, and adoption of governance best practices.
• Contribute to strategic data transformation and process improvement initiatives across the broader data organization.
• Collaborate across business, product, data, technology, Legal, and Risk teams to improve data discoverability, understanding, integration, protection, and responsible use.
• Explore opportunities to apply AI-enabled tools and approaches to improve governance processes, operational efficiency, and data management practices.

Requirements:

• Bachelor’s degree or equivalent professional experience in Data Management, Information Management, Business, Finance, Computer Science, or a related discipline.
• Proven experience in Data Governance, Data Quality, Data Management, or a closely related field.
• Experience working with Ownership, Individuals, Sanctions, or comparable regulatory and relationship data, including complex ownership structures, entity relationships, individual/contact information, and regulatory attributes.
• Strong understanding of Data Governance, Data Quality, Metadata Management, and Master Data Management principles and practices.
• Demonstrated experience defining and implementing data quality controls, measurements, monitoring frameworks, and remediation processes.
• Experience developing or maintaining metadata, data lineage, data catalogs, business glossaries, or data quality tooling is preferred.
• Familiarity with Structured Query Language (SQL) and data analysis techniques is advantageous.
• DAMA Certified Data Management Professional or another relevant data management certification is preferred.
• Strong analytical and problem-solving abilities, with excellent communication and stakeholder-management skills.
• Ability to manage multiple priorities, navigate ambiguity, and collaborate effectively across business and technology teams.
• Demonstrated ability to influence stakeholders, facilitate governance discussions, and promote accountability without relying solely on formal authority.
• Basic understanding of artificial intelligence concepts, with curiosity about how AI tools can improve processes and efficiency.
• Interest in developing knowledge of responsible AI practices, including AI risk management, governance, and ethical use.

Benefits:

• Salary: $103,800–$150,600 USD base salary for U.S.-based positions, depending on experience, education, skills, level, and location.
• Incentive compensation: Eligibility for additional incentive compensation beyond base salary.
• Healthcare: Medical, dental, and vision coverage.
• Retirement: 401(k) plan with opportunities for employee and employer contributions.
• Paid time off: Paid time off and parental leave.
• Insurance: Life, disability, and accident insurance options.
• Employee stock purchase: Access to a discounted employee stock purchase plan.
• Education: Tuition reimbursement to support continued professional development.
• Career growth: Opportunities to contribute to strategic data transformation, governance, analytics, AI, and enterprise data initiatives.
• Inclusive workplace: Commitment to equal opportunity, diverse perspectives, accessibility, and reasonable workplace accommodations.
• Mission-driven environment: Work on data capabilities that support informed decision-making, regulatory compliance, responsible AI, and globally used products and services.