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Data Governance Analyst

Building the frameworks that keep an organisation's data accurate, owned, and trusted

Also known as:Data StewardData Quality AnalystMaster Data AnalystData Management AnalystMDM Analyst
Growing

Data Governance Analyst Salary

United Kingdom

£40,000 – £70,000

United States

$70,000 – $115,000

Varies by location, sector, and experience. Last updated: 2025.

What Is a Data Governance Analyst?

A Data Governance Analyst develops and maintains the frameworks, policies, and processes that ensure an organisation's data is accurate, consistent, well-documented, and used appropriately. The role is responsible for the practical implementation of data governance — defining data ownership, maintaining business glossaries and data dictionaries, implementing data quality rules, managing metadata, and ensuring that data assets across the organisation can be trusted and traced to their source.

Data Governance is growing rapidly as a discipline — driven by regulatory requirements, the increasing reliance on data for AI and analytics, and the reputational risk of poor data quality. Data Governance Analysts work closely with data engineers, business analysts, and compliance teams to embed governance practices into data pipelines and platform tooling. The role is less technical than data engineering but more so than pure policy work — practitioners need enough understanding of how data flows through systems to implement governance controls effectively, and enough communication skill to drive adoption across business and technical teams.

What Does a Data Governance Analyst Do?

  • Develop and maintain data governance policies, standards, and procedures to establish consistent data management practices organisation-wide
  • Build and maintain the business glossary and data dictionary, defining key data terms, ownership, and authoritative sources
  • Implement and monitor data quality rules across critical data assets and report quality metrics to data owners and leadership
  • Manage data lineage documentation, tracing data flows from source systems through transformation layers to analytical consumption points
  • Conduct data audits to identify gaps in governance coverage and assess compliance with internal policies and regulatory requirements
  • Support data management compliance requirements including GDPR and BCBS 239, coordinating with legal, risk, and data engineering teams

Data Governance Analyst Skills

Hard Skills

  • Data Governance
  • Data Quality Management
  • Data Architecture
  • Master Data Management
  • Regulatory Compliance
  • Policy Documentation
  • Stakeholder Management
  • Workflow Analysis
  • Audit Management
  • Requirements Gathering

Soft Skills

  • Analytical ThinkingTracing data quality issues to source systems
  • Influence Without AuthorityDriving governance adoption across business teams
  • CommunicationTranslating policy requirements for technical and business audiences
  • Attention to DetailMaintaining accurate data dictionaries and ownership records
  • CollaborationWorking across data engineering, compliance, and analytics
  • Documentation DisciplineMaintaining business glossaries and metadata standards

Data Governance Analyst Tools & Software

How to Become a Data Governance Analyst

Typical Route

Most Data Governance Analysts hold a bachelor's degree in Information Systems, Business Administration, or Computer Science. The role accepts both technical and non-technical backgrounds — Management Information Systems programs at Indiana University's Kelley School of Business, the University of Arizona, and Carnegie Mellon's Heinz College are well aligned. A master's degree in Information Systems, Data Management, or Business Analytics supports progression into senior governance and data stewardship roles, particularly in regulated industries such as healthcare and financial services.

Alternative Route

DAMA Certified Data Management Professional (CDMP) is the most widely recognised data governance credential; self-study through the DAMA-DMBOK is the standard preparation route. Collibra University and Alation certifications support platform-specific competence. Microsoft Purview certifications are valued in Microsoft-stack organisations; Pluralsight offers structured preparation. Many practitioners develop governance expertise through data steward or data quality analyst roles — framework study alongside on-the-job exposure is the well-established entry route.

A Day in the Life of a Data Governance Analyst

Morning

Facilitate a data stewardship session with the finance team to resolve conflicting definitions of "net revenue" appearing in three different source systems and the BI layer
Audit the customer data domain for lineage gaps and identify two transformation steps in the CRM-to-warehouse pipeline that have no documented owner or business rule
Update the business glossary with twelve new terms agreed in last week's cross-functional working group, assigning data owners and linking each term to its source system

Afternoon

Implement a new data quality rule on the product master dataset checking for duplicate SKUs and configure alerting to notify the data owner when the threshold is breached
Review a new data sharing agreement with a third-party analytics partner against the organisation's GDPR data transfer policy and flag two clauses requiring legal clarification
Prepare the quarterly data quality scorecard for the data leadership team, summarising rule pass rates, open issues, and the three data domains with the largest quality gaps

Data Governance Analyst Career Path

Data Analyst / Business Analyst

0–2 yrs

→

Data Governance Analyst

2–5 yrs

→

Senior Data Governance Analyst

5–7 yrs

→

Data Governance Manager / Data Steward Lead

7+ yrs

→

Head of Data Governance / Chief Data Officer

10+ yrs

Data Governance Analyst Job Outlook

Growing

Data Governance is growing as organisations recognise that AI and analytics initiatives built on poor-quality data consistently underperform or fail. Regulatory pressure — data protection law, banking risk standards, and emerging AI governance frameworks — is accelerating investment in data governance programmes. Practitioners who combine governance framework knowledge with hands-on data catalogue and quality tooling experience are in the strongest market position.

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