Data Semantics Architect: Taxonomies & Ontologies, Zero Trust

Red Arch Solutions; Reston (VA); On-site; USD 220,000 - 250,000; Full time

Job summary

Red Arch Solutions seeks a Data Semantics Architect to drive enterprise semantic frameworks, including taxonomies, ontologies, and metadata strategies, aligning with ICD 504 and Zero Trust objectives.

You will lead AoAs, collaborate with governance and security teams, and establish standards for data classification, tagging, and interoperability across systems and partners. A strong data governance background is essential.

Qualifications

• Development of enterprise taxonomies, ontologies, and semantic models.
• Definition of relationships between data entities and business concepts.
• Establishment of standards for semantic consistency across data assets.
• Support for metadata frameworks, tagging strategies, and data classifications.
• Experience with ICD 504, data governance, and Zero Trust security requirements.

Responsibilities

• Lead taxonomy, ontology, and semantic modeling efforts for enterprise data assets.
• Design and implement data tagging and metadata strategies for governance and ABAC.
• Evaluate frameworks and best practices through AoA and present recommendations to stakeholders.
• Collaborate with Security and Data Governance teams to enable data-centric security and Zero Trust.
• Promote interoperability and governance alignment across systems and partners.

Skills

Taxonomy Development

Ontology Development

Semantic Modeling

Metadata Management

Data Tagging

Controlled Vocabularies

Information Architecture

Data Governance

Education

Bachelor’s degree in Computer Science / Information Systems / Data Science with 16+ years experience

Job description

Red Arch Solutions seeks a Data Semantics Architect to drive enterprise semantic frameworks, including taxonomies, ontologies, and metadata strategies, aligning with ICD 504 and Zero Trust objectives.

You will lead AoAs, collaborate with governance and security teams, and establish standards for data classification, tagging, and interoperability across systems and partners. A strong data governance background is essential.