The Role
Develops enterprise taxonomies, ontologies, semantic models, metadata frameworks, and data-tagging strategies. Leads analyses of alternatives for semantic technologies and interoperability approaches, supports data governance and information sharing, and partners with security teams on ABAC, Zero Trust, classification, and data-centric security. Provides technical recommendations and establishes standards for data discoverability, interoperability, access control, and semantic consistency across Federal, DoD, or Intelligence Community environments.
Summary Generated by Built In
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
Core
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
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.
- 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.
- 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.
- 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.
- 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.
Core
- Taxonomy Development
- Ontology Development
- Semantic Modeling
- Metadata Management
- Data Tagging
- Controlled Vocabularies
- Information Architecture
- Data Governance
- ICD 504
- Information Sharing
- Data Interoperability
- Data Standards
- Metadata Standards
- Zero Trust Concepts
- ABAC
- Data Classification
- Data Labeling
- Data-Centric Security
- 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
Skills Required
- Bachelor's degree in computer science, information systems, information management, data science, or a related field
- Minimum 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 supporting data discoverability, interoperability, information sharing, and Zero Trust data-centric security
- Experience working within Federal, DoD, or Intelligence Community environments
- Taxonomy development
- Ontology development
- Semantic modeling
- Metadata management
- Data tagging and controlled vocabularies
- Information architecture and data governance
- ICD 504, information sharing, data interoperability, data standards, and metadata standards
- Zero Trust concepts, ABAC, data classification, data labeling, and data-centric security
- Analysis of Alternatives, requirements analysis, stakeholder engagement, and technical assessments
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The Company
What We Do
Red Arch Solutions is a premier U.S. small business providing its customers with state-of-the-art tactical and strategic intelligence, systems, and software engineering solutions, solving some of the most pressing and unique intelligence community challenges related to National Security. Our employees are exceptionally skilled professionals; individuals who are dedicated to collecting, analyzing, creating and engineering the best solutions in support of critical missions. Red Arch Solutions takes pride in the success of our customers. The depth of our engineers’ experience combined with our breadth of exposure across the intelligence community enables us to provide value added, synergistic analytical and engineering support. Unique to Red Arch Solutions is the focus on its employees. Our guiding principle is “People First.” We offer employees career mobility and stability, work-life balance flexibility, and individualized career paths. The loyalty of highly trained, skilled professionals is our key corporate asset. Red Arch Solutions is an Equal Opportunity Affirmative Action Employer.
