Metadata & Data Catalogs: Evaluate metadata management approaches, data catalogs, dictionaries, and common data definitions to improve enterprise data discovery and accessibility.
Ontologies & Semantic Data: Assess ontologies, taxonomies, semantic relationships, and data standards to support consistent interpretation and integration of mission data.
Data Integration & Interoperability: Analyze data flows, interfaces, mappings, and transformation approaches to identify dependencies, integration gaps, and technical risks.
Data Quality & Governance: Evaluate data quality, provenance, lineage, classification, and governance approaches to support reliable and traceable enterprise data.
Analytics & Emerging Capabilities: Assess data readiness and technical approaches supporting advanced analytics, automation, artificial intelligence, and machine learning.
Technical Requirements & Coordination: Collaborate with engineers, architects, developers, and mission stakeholders to define data requirements, evaluate proposed solutions, and resolve technical issues.
Engineering Assessment & Validation: Support technical reviews, testing assessments, and validation activities to evaluate data capabilities against requirements and mission objectives.
Government Decision Support: Develop technical assessments, documentation, recommendations, and briefings to inform Government decisions on enterprise data capabilities.
Qualifications
Required Qualifications
Clearance: Must possess and be able to maintain a TS/SCI with Polygraph.
Education & Experience: Bachelor's degree with 5-7 years of relevant experience; OR a Master's degree with 3-5 years of experience; OR PhD with 0-2 years of experience.
Data Architecture & Structures: Working knowledge of data models, schemas, relational databases, data structures, and integration principles.
Data Management: Understanding of metadata, data quality, data classification, and enterprise data organization concepts.
Technical Proficiency: Familiarity with SQL, Python, or comparable data analysis and processing technologies, sufficient to assess technical approaches and data workflows.
Systems Analysis: Ability to evaluate technical solutions, identify dependencies and risks, and contribute to engineering assessments and recommendations.
Communication & Collaboration: Strong analytical, documentation, and communication skills with the ability to work across multidisciplinary technical teams.
Desired Qualifications
Metadata & Semantic Technologies: Familiarity with data catalogs, ontologies, taxonomies, knowledge graphs, semantic models, or metadata management platforms.
Data Standards & Technologies: Understanding of RDF, OWL, SPARQL, JSON, XML, APIs, or related data representation and integration technologies.
Enterprise Data Platforms: Exposure to data lakes, warehouses, cloud-based data platforms, or distributed data architectures.
Data Governance: Familiarity with data lineage, provenance, master data management, data stewardship, or enterprise data standards.
Analytics & AI/ML: Understanding of statistical analysis, machine learning, AI-enabled applications, or data visualization techniques.
Mission Environment: Experience supporting Intelligence Community (IC) or DoD systems, enterprise integration, or Agile/DevSecOps environments.
Equal Pay Act
This is the projected compensation range for this position. There are differentiating factors that can impact a final salary/hourly rate, including, but not limited to, Contract Wage Determination, relevant work experience, skills and competencies that align to the specified role, geographic location (For Remote Opportunities), education and certifications as well as Federal Government Contract Labor categories. In addition, Arcfield invests in its employees beyond just compensation. Arcfield ’s benefits offerings include, dependent upon position, Health Insurance, Life Insurance, Paid Time Off, Holiday Pay, Short Term and Long-Term Disability, Retirement and Savings, Learning and Development opportunities, wellness programs as well as other optional benefit elections.
- Min: $94,910.76
- Max: $165,031.40
- EEO Statement
We are an equal opportunity employer and federal government contractor. We do not discriminate against any employee or applicant for employment as protected by law.
The Mission
At Arcfield, we provide foundational systems engineering and integration solutions that protect and advance the nation’s most critical space and ground missions. We are currently seeking an Enterprise Data Scientist to provide Systems Engineering and Technical Assistance (SETA) support for enterprise data architecture, management, and integration within the Ground Enterprise Directorate.
The Role
In this role, you will provide technical analysis and engineering advisory support to help the Government organize, integrate, and effectively leverage complex mission data across enterprise systems. You will evaluate data models, schemas, metadata, ontologies, and data catalogs to ensure technical approaches support interoperability, accessibility, consistency, and mission requirements.
The ideal candidate has a strong technical foundation in data science and data architecture, with the ability to assess proposed solutions, identify integration challenges, and recommend practical improvements. Working alongside experienced systems engineers, architects, developers, and Government stakeholders, you will help ensure enterprise data capabilities are technically sound, scalable, and aligned with mission objectives.
Key Responsibilities
Data Architecture & Modeling: Assess data models, schemas, structures, and relationships for consistency, interoperability, and alignment with enterprise requirements.
Metadata & Data Catalogs: Evaluate metadata management approaches, data catalogs, dictionaries, and common data definitions to improve enterprise data discovery and accessibility.
Ontologies & Semantic Data: Assess ontologies, taxonomies, semantic relationships, and data standards to support consistent interpretation and integration of mission data.
Data Integration & Interoperability: Analyze data flows, interfaces, mappings, and transformation approaches to identify dependencies, integration gaps, and technical risks.
Data Quality & Governance: Evaluate data quality, provenance, lineage, classification, and governance approaches to support reliable and traceable enterprise data.
Analytics & Emerging Capabilities: Assess data readiness and technical approaches supporting advanced analytics, automation, artificial intelligence, and machine learning.
Technical Requirements & Coordination: Collaborate with engineers, architects, developers, and mission stakeholders to define data requirements, evaluate proposed solutions, and resolve technical issues.
Engineering Assessment & Validation: Support technical reviews, testing assessments, and validation activities to evaluate data capabilities against requirements and mission objectives.
Government Decision Support: Develop technical assessments, documentation, recommendations, and briefings to inform Government decisions on enterprise data capabilities.
Required Qualifications
Clearance: Must possess and be able to maintain a TS/SCI with Polygraph.
Education & Experience: Bachelor's degree with 5-7 years of relevant experience; OR a Master's degree with 3-5 years of experience; OR PhD with 0-2 years of experience.
Data Architecture & Structures: Working knowledge of data models, schemas, relational databases, data structures, and integration principles.
Data Management: Understanding of metadata, data quality, data classification, and enterprise data organization concepts.
Technical Proficiency: Familiarity with SQL, Python, or comparable data analysis and processing technologies, sufficient to assess technical approaches and data workflows.
Systems Analysis: Ability to evaluate technical solutions, identify dependencies and risks, and contribute to engineering assessments and recommendations.
Communication & Collaboration: Strong analytical, documentation, and communication skills with the ability to work across multidisciplinary technical teams.
Desired Qualifications
Metadata & Semantic Technologies: Familiarity with data catalogs, ontologies, taxonomies, knowledge graphs, semantic models, or metadata management platforms.
Data Standards & Technologies: Understanding of RDF, OWL, SPARQL, JSON, XML, APIs, or related data representation and integration technologies.
Enterprise Data Platforms: Exposure to data lakes, warehouses, cloud-based data platforms, or distributed data architectures.
Data Governance: Familiarity with data lineage, provenance, master data management, data stewardship, or enterprise data standards.
Analytics & AI/ML: Understanding of statistical analysis, machine learning, AI-enabled applications, or data visualization techniques.
Mission Environment: Experience supporting Intelligence Community (IC) or DoD systems, enterprise integration, or Agile/DevSecOps environments.
