Director, Data Governance & Metadata

Career Guide

A Director of Data Governance & Metadata sets the rules, ownership, and quality standards for an organization’s data, and builds systems so people can easily find, understand, and trust it. The role typically leads programs like data cataloging (metadata), data definitions, data quality measurement, access rules, and compliance support, working across IT, analytics, security, legal/compliance, and business teams.

Browse All Roles

Key Responsibilities

Define and lead the company-wide data governance program (decision-making model, roles, policies, and how issues get resolved).
Establish data ownership and stewardship: clarify who is responsible for key datasets and business definitions.
Build and scale a metadata strategy (data catalog, business glossary, data lineage) so users can discover and understand data.
Set data quality standards and monitoring (what “good” looks like, how it’s measured, how problems are fixed, and how trends are reported).
Partner with Security, Privacy, and Legal to support regulatory needs (e.g., handling sensitive data, retention, access approvals, audits).
Create clear data definitions and naming standards to reduce inconsistent reporting and “multiple versions of the truth.”
Oversee governance tooling selection and adoption (data catalog, quality tools, workflow/ticketing integrations).
Drive change management: training, communications, and incentives so teams actually use governance processes and tools.
Set program KPIs (catalog coverage, definition adoption, quality score trends, issue resolution time) and report progress to leadership.
Manage a team and budget; coordinate with platform/data engineering leaders to align governance with the data architecture.

Top Skills for Success

Program leadership and stakeholder management (aligning many teams on shared rules and priorities)

Policy writing and practical governance design (turning principles into simple, usable processes)

Metadata management (data catalog, glossary, ownership, and “how to interpret this data” documentation)

Data quality management (defining checks, prioritizing issues, and tracking improvement)

Data privacy and security fundamentals (sensitive data handling, access controls, audit readiness)

Data architecture literacy (how data flows from source systems to reports/analytics; lineage concepts)

Change management and adoption (training, communications, and making governance easy to follow)

Metrics and ROI storytelling (showing business impact like fewer reporting disputes and faster delivery)

Tooling evaluation and rollout (catalog, quality, workflow, and integration planning)

Vendor and budget management (contracts, renewals, prioritizing spend)

Career Progression

Can Lead To

VP / Head of Data Governance

Chief Data Officer (CDO)

VP / Head of Data Management

Head of Data Quality

Head of Data Strategy

Transition Opportunities

Director / Head of Data Platform (if strong technical background)

Director of Analytics Enablement / BI Governance

Director of Risk, Compliance, or Data Privacy (in regulated industries)

Product Leader for Data Products (ownership and standards applied to data-as-a-product)

Common Skill Gaps

Often Missing Skills

Clear operating model: who decides what, and how exceptions are handledPractical metadata coverage (catalog adoption stalls without simple workflows and ownership)Data quality prioritization (too many checks; not tied to business impact)Measuring outcomes (limited KPIs that show reduced risk or faster delivery)Change management (policies written but not adopted)Privacy/security alignment (unclear rules for sensitive data classification and access approvals)Integration with engineering workflows (governance not embedded in delivery processes)

Development SuggestionsBuild a lightweight governance playbook (roles, decision rights, definitions process, quality issue workflow). Pick 1–2 high-value domains (e.g., customer, product, finance) and deliver measurable wins: catalog coverage, agreed definitions, and quality score improvements tied to real business pain. Embed governance steps into existing tools (ticketing, data pipelines, access request processes) so it becomes part of daily work rather than a separate activity.

Market Intelligence Report

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

See the market intelligence report

Salary & Demand

Median Salary Range

Entry Level$150k–$200k USD (smaller orgs or first-time director scope)

Mid Level$200k–$260k USD

Senior Level$260k–$350k+ USD (large enterprises; may include bonus/equity)

Growth Trend

Strong and growing. Demand is driven by increased regulation, rising AI/analytics adoption (which requires trusted data), cloud migrations, and a greater focus on controlling data access and quality at scale.

Companies Hiring

Major Employers

JPMorgan ChaseBank of AmericaWells FargoCitiUnitedHealth GroupCVS HealthHumanaPfizerMerckComcastVerizonAT&TWalmartAmazonMicrosoft

Industry Sectors

Banking and financial servicesInsuranceHealthcare providers and payersPharmaceuticals and life sciencesTelecommunicationsRetail and e-commerceTechnology and cloud servicesEnergy and utilitiesGovernment and public sector

Recommended Next Steps

Create or refine a 12-month roadmap with 3–5 measurable outcomes (e.g., % of critical data elements with owners and definitions; reduction in recurring reporting issues).

Inventory critical data domains and rank them by business risk and value; start governance where impact is highest.

Standardize data definitions via a business glossary and set an approval workflow with named owners.

Implement a data catalog approach (or improve adoption) with required fields: owner, definition, sensitivity level, and trusted sources.

Launch a data quality scorecard for priority datasets and set a process for issue intake, triage, and resolution.

Align with Security/Privacy on sensitive data classification, access rules, and audit-ready documentation.

Build a short enablement plan: office hours, training for stewards, and simple templates for definitions and quality rules.

Prepare an executive-friendly dashboard to report progress and outcomes monthly (risk reduced, time saved, fewer disputes).