Director Data Governance Manager - Data Steward

At Moody's, we unite the brightest minds to turn today’s risks into tomorrow’s opportunities. We do this by striving to create an inclusive environment where everyone feels welcome to be who they are—with the freedom to exchange ideas, think innovatively, and listen to each other and customers in meaningful ways. Moody’s is transforming how the world sees risk. As a global leader in ratings and integrated risk assessment, we’re advancing AI to move from insight to action—enabling intelligence that not only understands complexity but responds to it. We decode risk to unlock opportunity, helping our clients navigate uncertainty with clarity, speed, and confidence.

If you are excited about this opportunity but do not meet every single requirement, please apply! You still may be a great fit for this role or other open roles. We are seeking candidates who model our values: invest in every relationship, lead with curiosity, champion diverse perspectives, turn inputs into actions, and uphold trust through integrity. 

Skills and Competencies

• 8+ years of relevant professional experience in data governance, data stewardship, data quality, master and reference data, data controls, or product data management, including leading teams and complex cross-functional initiatives
• Deep knowledge of business-entity and relationship data, including subsidiaries and corporate hierarchies, shareholders and beneficial ownership, persons, officers and directors, news and media, sanctions and watchlists, and other relationships among legal entities and individuals
• Strong command of data governance and stewardship practices consistent with DAMA-DMBOK and EDM Council DCAM, including ownership and decision rights, policies and standards, critical data elements, business definitions, metadata, lineage, lifecycle management, issue management, and change control
• Proven ability to design and operationalize data quality controls, including defining quality dimensions and thresholds, designing executable tests, selecting control points within ETL and data pipelines, enabling human-in-the-loop exception management, and defining remediation, root-cause analysis, and closure criteria, supported by working knowledge of data catalogs, data quality platforms, workflow and ticketing tools, SQL, ETL technologies, and cloud data platforms
• Strong product, customer, and commercial orientation, with the ability to translate customer use cases and product needs into measurable data requirements and to connect data quality, coverage, and provenance to product differentiation, customer value, revenue, and commercial strategy
• Demonstrated leadership in people management, program management, and change management, including directing teams and matrixed partners, transitioning new controls into sustainable operations, and communicating complex issues, trade-offs, residual risk, and investment needs to technical and non-technical audiences across multiple layers of the organization
• Deep expertise in and genuine enthusiasm for artificial intelligence, with a track record of championing AI adoption and embedding AI into data quality assurance and audit workflows to detect data errors at scale, including profiling, anomaly detection, relationship and ownership-structure analysis, and prioritization of exceptions for human review, while measuring detection accuracy and reducing false positives over time
• Demonstrated leadership in using AI to correct data errors in controlled and governed ways, including AI-assisted correction, enrichment, and remediation recommendations with defined confidence thresholds, human-in-the-loop approval, audit trails, and validation before publication, and in managing AI-related risks, ensuring ethical governance, and fostering a culture of responsible AI adoption across stewardship and operations teams 

Education

• Bachelor’s degree in Data Management, Information Systems, Computer Science, Business, Finance, Economics, or a related field required; equivalent professional experience may be considered
• Advanced degree or relevant professional certification, such as CDMP, DCAM, data quality, project management, process improvement, or change management, preferred 

Responsibilities

Lead governance, quality controls, and stewardship of business-entity relationship data, from customer requirements through sustained production use. 

• Lead the stewardship and day-to-day governance of business-entity relationship data domains, establishing business definitions, data-element standards, critical data elements, ownership, decision rights, permitted values, sourcing expectations, and lifecycle rules, and chairing domain governance forums to resolve cross-functional data decisions
• Partner directly with customers, Product Management, Product Development, Sales, Client Service, Commercial Strategy, and peer data stewards for other data domains to understand how data is used, define fitness-for-use expectations, and translate customer evidence, product performance, and commercial outcomes into governed requirements and investment priorities
• Define data quality rules, thresholds, and acceptance criteria aligned with approved policies and standards, and design detailed tests that identify records and relationships not meeting those standards; provide engineering teams with complete, testable requirements, validate developed logic, and lead user acceptance testing
• Lead the design and implementation of an end-to-end data quality controls architecture that systematically identifies data quality errors, working with process-mapping specialists, engineers, and operations teams to establish detective and preventive control points across ETL and data pipelines where records and relationships are tested against approved standards, failures are logged and prioritized by severity and customer impact, and actionable exceptions are routed to the human-in-the-loop accountable for resolution
• Define the remediation path for each category of detected error, specifying the required disposition (such as correction, enrichment, reprocessing, source challenge, suppression, or exception approval), decision rules, supporting evidence, escalation thresholds, and closure criteria to be executed by the separate remediation team, and lead root-cause analysis of recurring errors to drive durable preventive action into sources, processes, and controls
• Transition the controls architecture into business-as-usual operations by equipping the remediation team with procedures, service levels, training, and hypercare support; confirm the team can triage and resolve detected errors at the frequency each control requires; and own the ongoing effectiveness of the architecture by measuring detection accuracy, remediation timeliness, and error recurrence, and recalibrating tests, control points, and remediation paths as data, sources, use cases, regulations, and customer expectations evolve
• Manage, coach, and develop a team of data stewards while directing and evaluating work delivered by matrixed teams; communicate control performance, customer impact, residual risk, and investment needs to senior leadership; and maintain auditable documentation and reusable stewardship methods, including the responsible use of AI 

About the Team

The Moody’s Analytics Data Estate Data Governance team helps ensure that data is trusted, consistent, well understood, and used responsibly as a business asset. The team sets governance policies, standards, decision rights, and accountability; supports data ownership and stewardship; develops shared data models; and strengthens data quality, metadata, lineage, reference and master data, and lifecycle practices. Working across business, product, data, technology, Legal, Risk, Operations, Sales, Client Service, and customers, it turns enterprise data strategy into practical controls and ways of working that make data easier to find, understand, combine, protect, and use for products, analytics, artificial intelligence, regulatory compliance, and business decisions. Because Moody’s sells data and data-enabled products, the team connects governance and control performance directly to customer outcomes, product development, and commercial strategy. 

Moody’s is an equal opportunity employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, national origin, disability, protected veteran status, sexual orientation, gender expression, gender identity or any other characteristic protected by law.

Candidates for Moody's Corporation may be asked to disclose securities holdings pursuant to Moody’s Policy for Securities Trading and the requirements of the position. Employment is contingent upon compliance with the Policy, including remediation of positions in those holdings as necessary.