Data Engineer Architect

What You'll Do

• Design and develop JSON Schema representations of the core data objects, attributes, validation rules, and relationships that underpin the Program Protection process.
• Build validation examples, test fixtures, and versioning guidance so the schema can grow iteratively as the domain model matures.
• Develop a formal ontology (OWL/RDF or equivalent) that standardizes terminology and captures relationships across data objects, making the model usable across organizations.
• Collaborate closely with domain SMEs to ensure the data model faithfully represents the real-world semantics, constraints, and dependencies they work with daily.
• Write and maintain technical documentation, including data-model guides, schema usage references, and integration patterns, for both practitioners and future developers.
• Identify and resolve data-quality issues such as duplication, inconsistency, ambiguous definitions, and gaps in the source material.
• Support workflow definition by specifying the data objects consumed and produced at each step, ensuring traceability between the workflows and the underlying schema.
• Ensure all deliverables are open, non-proprietary, and provided with full Government data rights, with no vendor lock-in or licensing constraints.

What We're Looking For

• 5+ years of professional experience in data engineering, data architecture, or knowledge engineering.
• Strong proficiency with JSON Schema, including experience designing schemas from scratch rather than only consuming existing ones.
• Hands-on experience building or working with formal ontologies (OWL, RDF, SKOS) or controlled vocabularies in a professional setting.
• Deep understanding of data-modeling fundamentals: normalization, entity-relationship design, attribute taxonomies, and schema evolution strategies.
• Proven ability to collaborate with domain experts who think in documents and processes rather than data structures, and to translate their knowledge into structured, maintainable models.
• Comfortable with Git, documentation-as-code workflows, and collaborative development practices.
• Active Secret clearance or ability to obtain one prior to start.

Nice to Have

• Experience in DoW acquisition, systems security engineering, or program protection environments.
• Familiarity with Program Protection concepts such as CPI, critical functions, security classification, or Anti-Tamper, even at a general level.
• Hands-on experience with knowledge-graph technologies, SPARQL, or graph databases.
• Background with NIST frameworks (800-171, 800-53) or other federal information-security standards.
• Prior experience building data models intended for multi-organization or cross-vendor use.
• Interest in expanding into ML/AI data pipelines, digital twins, or model-based systems engineering.

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