Enterprise Data Modeler at SAIC

Chantilly, Virginia, United States -

Full Time

Start Date

Immediate

Expiry Date

22 May, 26

Salary

0.0

Posted On

21 Feb, 26

Experience

5 year(s) or above

Remote Job

Yes

Telecommute

Yes

Sponsor Visa

Skills

Data Modeling, Data Architecture, Systems Engineering, Technical Advisory, Cloud Services, AWS, Data Ingestion, Data Storage, RBAC/ABAC, Data Science Analytics, Data Governance, Systems Analysis, SAFe Agile, Requirements Gathering, Data Integration, Technical Briefings

Industry

Defense and Space Manufacturing

Description

SAIC is seeking a Enterprise Data Modeler to provide Systems Engineering and Technical Advisory (SETA) support to a mission critical program in Chantilly, VA. In this role, you will directly support the National Reconnaissance Office’s (NRO) Ground Enterprise Directorate (GED)—the organization responsible for architecting, acquiring, and sustaining the nation’s most advanced space and ground systems across their full lifecycle. All candidates must hold an active TS/SCI clearance with Polygraph. As the Enterprise Data Modeler, you will help the customer acquire and integrate multi‑INT, cloud‑based data services across multiple enclaves. You will shape enterprise data architecture, enable mission‑focused tools, and drive automation, interoperability, and information sharing to support strategic decision‑making. Key Responsibilities to include: Drive the technical and architectural direction of the enterprise data evolution roadmap, including data ingestion, storage, reporting, MLS solutions, RBAC/ABAC access controls, security markings, and data science analytics. Gather, decompose, and refine requirements, guiding stakeholders toward best practices for building modern, scalable data solutions—primarily leveraging the AWS technology stack. Partner directly with application teams to propose, define, implement, and track new mission aligned data solutions and emerging technologies. Create conceptual, logical, and physical data models, define data domains, propose data standards, and oversee data integration, pipelines, and access methods. Analyze structured and semi structured data from diverse sources; design and manage enterprise data models and processes; and develop new data flows to support mission analytics. Execute a robust data governance program, ensuring enterprise data is leveraged for mission value while adhering to compliance and security requirements. Apply systems analysis and design methodologies to identify technical debt, architectural runway, and efficiency trade offs across current and proposed cloud based system designs. Develop technical briefings and documentation, including data roadmaps, architectural artifacts, and acquisition strategies to support program planning and execution. Support SAFe Agile processes, collaborating with government teams, development contractors, user engagement teams, and mission stakeholders to advance enterprise data capabilities. Required Education and Experience Bachelors and nine (9) years or more experience; Masters and seven (7) years or more experience ; PhD or JD and four (4) years or more experience. Relevant experience to be substituted in lieu of degree. Active Top Secret Clearance with Polygraph. 3+ years of experience in data modeling and/or data architecture. Strong engineering background with knowledge of cloud software architecture, data management practices and IC/DOD ontologies. Experience supporting system architecture, design or development in an AWS/C2S environment. Domain knowledge in Agile software development practices. Demonstrated capability and success working in team environments. Strong oral and written communications ability on significant technical matters often requiring coordination within a high-tempo environment. Good working knowledge of MS Office applications.

Responsibilities

The Enterprise Data Modeler will drive the technical and architectural direction for enterprise data evolution, covering ingestion, storage, security controls, and analytics, while partnering with application teams to define and implement new mission-aligned data solutions.