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Data Governance Lead

Job in Town of Washington, Dutchess County, New York, USA
Listing for: Cleary Gottlieb Steen & Hamilton LLP
Full Time position
Listed on 2026-10-14
Job specializations:
  • IT/Tech
    Information Security & Data Protection, Change Management, Data Analyst, Data Warehousing
Salary/Wage Range or Industry Benchmark: 175000 - 200000 USD Yearly USD 175000.00 200000.00 YEAR
Job Description & How to Apply Below
Location: Town of Washington

Cleary Gottlieb is a pioneer in globalizing the legal profession. We have 14 offices in major financial centers around the world, but we operate as a single, integrated global partnership and not as a U.S. firm with a network of overseas locations. The firm employs approximately 1,100 lawyers from more than 50 countries. Since 1946 our lawyers and staff have worked across practices, industries, jurisdictions, and continents to provide clients with simple, actionable approaches to their most complex legal and business challenges, whether domestic or international.

We support every client relationship with intellectual agility, commercial acumen, and a human touch.

Responsibilities Data Governance Operating Model
  • Lead the implementation and day-to-day operation of the Firm’s federated data governance operating model under the direction of the Director of Data Strategy and Governance.
  • Establish the processes, standards, procedures, roles, decision rights, governance forums, and escalation mechanisms through which the Firm governs data.
  • Clearly define and document the respective accountabilities of Data Owners, Data Stewards, technology custodians, and Data Governance to prevent ambiguity between business and governance responsibilities.
  • Establish repeatable governance processes for decisions, approvals, exceptions, escalations, cross-domain issues, and changes to governance standards.
  • Ensure governance processes enable business accountability rather than transferring ownership of business data or business decisions to IT or the Data Governance function.
  • Monitor adoption and effectiveness of the operating model and recommend improvements as the Firm’s governance practice matures.
Data Ownership and Stewardship
  • Establish and operationalize the Firm’s Data Owner and Data Steward model, including role definitions, decision rights, responsibilities, working practices, training, and supporting materials.
  • Enable Data Owners to exercise accountability for their domains by providing consistent processes for making and documenting decisions concerning data definitions, quality expectations, appropriate business use, priorities, and issue remediation.
  • Establish the processes and tools through which Data Stewards maintain business definitions, monitor data quality, maintain governance metadata, investigate issues, and support Data Owners.
  • Build and facilitate an active community of Data Owners and Data Stewards to promote consistent governance practices and shared learning across the Firm.
  • Identify gaps in ownership or stewardship and facilitate assignment or escalation to the appropriate business leadership.
  • Provide guidance and challenge where governance requirements are not being met while maintaining accountability with the appropriate business owner.
Data Quality Governance
  • Maintain the Firm-wide data quality governance framework, including common standards, quality dimensions, measurement approaches, issue severity criteria, reporting practices, and escalation processes.
  • Partner with Data Owners and Data Stewards to identify Critical Data Elements and establish appropriate quality requirements.
  • Facilitate the definition of data quality rules and thresholds by the Data Owners and subject‑matter experts who understand the business purpose and acceptable use of the data.
  • Establish repeatable processes for measuring, monitoring, prioritizing, escalating, and reporting data quality issues.
  • Develop data quality scorecards and governance metrics that provide Data Owners and leadership with visibility into quality performance, trends, risks, and remediation progress.
  • Facilitate root‑cause analysis of significant or recurring data quality issues and ensure remediation actions have clearly identified business and…
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