Head of Data Taxonomy and Ontology
Career GuideKey Responsibilities
- Define a company-wide taxonomy strategy for data, content, and business terms
- Create and maintain a business glossary with clear definitions and ownership
- Design and maintain an ontology that captures relationships between key concepts
- Set governance for naming standards, metadata quality, and change management
- Partner with Data Governance and Data Engineering to implement standards in platforms
- Work with Product and Analytics teams to align metrics and definitions
- Improve data discovery through better tagging, classification, and search signals
- Establish review workflows to prevent duplicate terms and conflicting definitions
- Measure adoption and data findability using clear success metrics
- Lead a team of taxonomy and ontology specialists, including hiring and coaching
Top Skills for Success
Data Governance
Metadata Management
Taxonomy Design
Ontology Modeling
Information Architecture
Stakeholder Management
Change Management
Data Quality Management
Semantic Search Concepts
Technical Writing
Program Management
Cross-functional Leadership
Career Progression
Can Lead To
Director of Data Governance
Director of Data Management
Director of Data Strategy
Head of Knowledge Management
Head of Search and Discovery
Head of Analytics Enablement
Transition Opportunities
Chief Data Officer
VP of Data and Analytics
VP of Data Governance
Head of AI Data Strategy
Enterprise Data Architect
Common Skill Gaps
Often Missing Skills
Ontology Engineering ToolsGraph Data ModelingEnterprise Data Catalog AdministrationData Stewardship Operating ModelsKPI DesignExecutive Communication
Development SuggestionsBuild hands-on experience by leading a glossary and taxonomy rollout in a data catalog, define governance workflows with stewards, and publish a clear measurement plan for adoption and findability. Strengthen executive communication with concise updates that tie taxonomy outcomes to time saved, reduced errors, and faster product delivery.
Salary & Demand
Median Salary Range
Entry LevelUSD 170,000 to 220,000
Mid LevelUSD 220,000 to 300,000
Senior LevelUSD 300,000 to 450,000
Growth Trend
Growing demand, especially in large enterprises modernizing data platforms and organizations scaling AI, search, and self-serve analytics. Hiring is most common in regulated industries and data-rich consumer businesses.Companies Hiring
Major Employers
GoogleMicrosoftAmazonAppleMetaSalesforceAdobeIBMOracleServiceNowSnowflakeDatabricksJPMorgan ChaseGoldman SachsUnitedHealth GroupCVS HealthPfizerRocheWalmartTarget
Industry Sectors
TechnologyFinancial ServicesHealthcarePharmaceuticalsRetail and EcommerceMedia and PublishingTelecommunicationsInsuranceGovernment and Public Sector
Recommended Next Steps
1
Audit current business terms and identify duplicates, conflicts, and missing definitions2
Create a prioritized taxonomy roadmap tied to the highest-value use cases3
Stand up a governance cadence with term owners and review workflows4
Implement naming standards and metadata requirements in the chosen catalog5
Pilot an ontology for one domain and expand after validation6
Define success metrics such as adoption, search success rate, and definition coverage7
Develop a training plan for analysts, engineers, and product teams8
Prepare an executive narrative that connects the work to business outcomes