Director, Data Governance & Standards

Career Guide

A Director of Data Governance & Standards sets the policies, rules, and operating model that ensure an organization’s data is trusted, well-defined, secure, and consistently used across teams. This role typically leads cross-functional programs (IT, analytics, security, legal, and business leaders) to improve data quality, define common data standards, and ensure compliance with regulations and internal controls.

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Key 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.

Market Intelligence Report

Director, Data Governance & Standards is part of the Data Governance category.Explore our market intelligence report to see how AI and hiring demand are shifting for these roles.

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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

Assess your organization’s current governance maturity (ownership, definitions, quality monitoring, access controls) and identify the top 3 gaps to address first

Create a 12-month roadmap with quick wins (e.g., critical data elements, top dashboards, key domains) and clear success metrics

Stand up or refresh a governance council with defined decision rights and a consistent cadence

Launch or improve a business glossary and data catalog adoption plan (who owns definitions, who approves changes)

Implement a repeatable data quality process: rules, monitoring, issue tracking, and root-cause remediation owners

Partner with Security/Privacy to align data classification, retention, and access review processes with governance

Develop a communications and training plan for stewards and data producers/consumers to drive adoption

Benchmark compensation and scope against similar enterprises; clarify team structure, budget, and tool ownership in job discussions

Prepare interview stories that show measurable outcomes, conflict resolution, and cross-functional execution