Director, Data Governance & Standards
Career GuideKey Responsibilities
- Define and lead the enterprise data governance strategy, including priorities, roadmap, and success metrics
- Establish data standards (common definitions, naming rules, formats) so teams interpret data the same way
- Create and run governance forums (councils/committees), decision rights, and escalation paths
- Oversee data quality programs: monitoring, issue management, root-cause fixes, and continuous improvement
- Partner with Security, Risk, and Legal on data privacy, retention, access rules, and regulatory compliance requirements
- Implement data stewardship roles and workflows so ownership and accountability are clear
- Guide data cataloging and metadata practices so users can find, understand, and trust data
- Align governance requirements with data platform teams (data warehouse/lake, integration, master data)
- Report on governance outcomes to executives: risk reduction, better reporting accuracy, faster access to trusted data
- Manage budget, vendors, and a team of governance leads, analysts, or stewards (depending on org size)
Top Skills for Success
Executive stakeholder management and influence across business and technical teams
Program leadership (roadmaps, prioritization, delivery tracking, and measurable outcomes)
Clear communication and change management to drive adoption of standards
Risk and compliance mindset (privacy, retention, access controls, audit readiness)
Data governance operating model design (decision rights, stewardship, policies, controls)
Data quality management (rules, monitoring, issue triage, root-cause remediation)
Data standards and definitions (business glossary, common metrics, reference data alignment)
Metadata and data catalog practices (lineage, ownership, definitions)
Working knowledge of data architecture and data platforms to align governance with implementation
Vendor/tool evaluation and implementation oversight (governance, catalog, quality, lineage tools)
Career Progression
Can Lead To
VP/Head of Data Governance
Chief Data Officer (CDO)
VP Data Management or Data Platforms
Chief Risk/Compliance Data Leader (in heavily regulated sectors)
Transition Opportunities
Director/Head of Data Management (Master Data, Reference Data, Data Quality)
Director of Data Strategy or Data Operating Model
Director of Analytics Enablement / Data Product Leadership
Data Privacy or Information Risk leadership roles (depending on background)
Common Skill Gaps
Often Missing Skills
Turning governance into measurable business outcomes (revenue, cost, risk reduction) rather than policy-only workDesigning a practical stewardship model that business teams actually adoptStrong metadata discipline (lineage, ownership, definitions) and scalable catalog practicesOperating effectively with modern data platforms (cloud data warehouses/lakes) while keeping controls lightweightBalancing privacy/security requirements with accessibility for analytics and AI use casesLeading through influence in matrixed organizations with limited direct authority
Development SuggestionsBuild a portfolio of before/after outcomes (e.g., reduced reporting errors, faster audit responses, improved data quality scores). Practice creating lightweight standards that remove ambiguity without slowing delivery. Strengthen comfort with common data platforms and governance tooling so policies map to real workflows. Regularly partner with Security/Privacy and key business leaders to align controls with value delivery.
Salary & Demand
Median Salary Range
Entry LevelUS$140k–$190k (smaller orgs or first-time director roles; often 8–12 years experience)
Mid LevelUS$190k–$250k (established programs; typical enterprise director scope)
Senior LevelUS$250k–$350k+ (large enterprises, regulated industries, global scope; may include bonus/equity)
Growth Trend
Strong and growing demand, driven by regulatory pressure (privacy and reporting), increasing AI/analytics adoption, and the need to reduce data risk while improving data reliability and speed-to-insight.Companies Hiring
Major Employers
JPMorgan ChaseBank of AmericaWells FargoCapital OneUnitedHealth Group / OptumCVS HealthAnthem / Elevance HealthKaiser PermanenteAmazonMicrosoftGoogleIBMOracleSalesforceWalmartTargetAT&TVerizonPfizerJohnson & JohnsonMerckComcastDeloitteAccenturePwCEYKPMG
Industry Sectors
Financial services (banking, payments, insurance)Healthcare providers and health insurersPharmaceuticals and life sciencesRetail and e-commerceTelecommunicationsTechnology and cloud platformsManufacturing and supply chain-heavy industriesConsulting and systems integratorsPublic sector and government agencies
Recommended Next Steps
1
Assess your organization’s current governance maturity (ownership, definitions, quality monitoring, access controls) and identify the top 3 gaps to address first2
Create a 12-month roadmap with quick wins (e.g., critical data elements, top dashboards, key domains) and clear success metrics3
Stand up or refresh a governance council with defined decision rights and a consistent cadence4
Launch or improve a business glossary and data catalog adoption plan (who owns definitions, who approves changes)5
Implement a repeatable data quality process: rules, monitoring, issue tracking, and root-cause remediation owners6
Partner with Security/Privacy to align data classification, retention, and access review processes with governance7
Develop a communications and training plan for stewards and data producers/consumers to drive adoption8
Benchmark compensation and scope against similar enterprises; clarify team structure, budget, and tool ownership in job discussions9
Prepare interview stories that show measurable outcomes, conflict resolution, and cross-functional execution