Data Semantics Architect

Position Summary
The Data Semantics Architect supports enterprise data management initiatives through the development of taxonomies, ontologies, semantic models, and data tagging strategies that improve data discoverability, interoperability, governance, and access control. The position leads analyses of alternatives (AoAs) and evaluates frameworks, standards, and approaches for structuring and classifying enterprise data assets in support of ICD 504, data governance, and Zero Trust objectives.
The Data Semantics Architect works closely with Data Governance SMEs, Data Stewards, Security teams, and Data Engineers to establish semantic frameworks that enable metadata-driven discovery, attribute-based access control (ABAC), and mission-focused analytics.
Key Responsibilities
Taxonomy & Ontology Development

• Develop and maintain enterprise taxonomies, controlled vocabularies, and ontologies.
• Define relationships between data entities, business concepts, and mission functions.
• Establish standards for semantic consistency across organizational data assets.
• Support development of common data definitions and business glossaries.

Data Tagging & Metadata Strategy

• Design enterprise data tagging and labeling frameworks.
• Define metadata models supporting governance, discovery, access control, and information sharing.
• Establish standards for data classification and attribute assignment.
• Support metadata enrichment and automated tagging capabilities.

Analysis of Alternatives (AoA)

• Lead AoAs evaluating semantic technologies, tagging approaches, metadata frameworks, and interoperability solutions.
• Analyze industry and government best practices for semantic modeling and data organization.
• Develop recommendations for implementation and adoption.
• Present findings and technical recommendations to stakeholders and governance bodies.

Zero Trust & Data-Centric Security

• Develop metadata structures that support Attribute-Based Access Control (ABAC).
• Partner with security teams to define data attributes used for policy enforcement.
• Support implementation of data-centric security controls and Zero Trust initiatives.
• Ensure tagging strategies aligning with classification, dissemination, and access requirements.

Data Governance & Interoperability

• Support enterprise data governance initiatives through semantic standardization.
• Align taxonomy and ontology efforts with ICD 504 and organizational information-sharing requirements.
• Promote interoperability across systems, domains, and mission partners.
• Support creation of authoritative semantic models and reference data structures.

Required Skills
Core

• Taxonomy Development
• Ontology Development
• Semantic Modeling
• Metadata Management
• Data Tagging
• Controlled Vocabularies
• Information Architecture
• Data Governance

Data Sharing & Policy

• ICD 504
• Information Sharing
• Data Interoperability
• Data Standards
• Metadata Standards

Security

• Zero Trust Concepts
• ABAC
• Data Classification
• Data Labeling
• Data-Centric Security

Strategic

• Analysis of Alternatives (AoA)

• Requirements Analysis

• Stakeholder Engagement

• Technical Assessments

• Data Standards & Semantics SME

Bachelor’s degree in computer science, Information Systems, Information Management, Data Science, or related field and a minimum of ten (16) years of experience supporting enterprise data management, metadata governance, taxonomy development, ontology engineering, semantic modeling, and data standards initiatives. Experience developing data tagging strategies, metadata frameworks, and semantic structures that support data discoverability, interoperability, information sharing, and Zero Trust data-centric security objectives within Federal, DoD, or Intelligence Community environments.
Salary for this role $220-250K #CJ