IT Data Architect

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IT Data Architect

Full Time DARPA HQ, Arlington, VA, US

Since 1958, DARPA has made pivotal investments in breakthrough technologies for national security. As the world changes dramatically – and even the pace of change itself increases – the agency seeks to engage the best minds and best ideas across specialties, communities, and disciplines to solve the greatest national security challenges on the horizon. DARPA brings together scientists, engineers, and tinkerers across the innovation ecosystem to push the bounds of technological possibility. The work we do is challenging by nature, but working with DARPA doesn’t have to be.

To make it happen, DARPA's program managers need highly skilled support contractors, broadly referred to as SETAs (Scientific Engineering and Technical Assistance) within DARPA. Often spanning programs, portfolios, and even offices in their impact, the SETAs help program managers chart and navigate the path toward groundbreaking discoveries. For the fortunate few who become part of the DARPA legacy, a time bound journey with the organization represents a unique and singular opportunity to alter the future. At DARPA, every day is a chance to make history. A chance to explore, discover, and invent. A chance to collaborate with pioneers in science and engineering contributing to an enduring mission.

The Data Architect must have 8 years of demonstrated experience in data architecture, data engineering, or enterprise systems design. Bachelor’s or Master’s degree in Computer Science, Data Engineering, Information Systems, or related field.Experience working in defense, intelligence, or other high-security environments. Strong knowledge of database systems (SQL/NoSQL), data warehousing, and distributed data platforms. Familiarity with cloud platforms (AWS GovCloud, Azure Government, etc.). Knowledge of data governance, data modeling, and architecture frameworks (e.g., TOGAF, DoDAF). Ability to build and maintain DevSecOps CI/CD build pipelines. Active Top Secret clearance is required.

Responsibilities will include, but are not limited to the following:

• Design and implement enterprise-level data architecture frameworks across defense systems and platforms
• Develop data models, standards, and governance policies to ensure consistency, quality, and integrity
• Integrate data from multiple classified and unclassified sources to support operational readiness and analysis
• Collaborate with cybersecurity teams to ensure compliance with security protocols and data protection regulations
• Support advanced analytics, AI/ML initiatives, and real-time data processing for research and strategic applications
• Establish metadata management, data lineage, and master data management practices
• Optimize data storage, retrieval, and processing for high-performance environments
• Lead data architecture reviews and provide technical guidance to engineering and analytics teams
• Ensure compliance with federal standards (e.g., DoD data strategy, security frameworks, interoperability requirements)
• Experience with big data technologies (Hadoop, Spark, Karka)

Preferred Qualifications

• Background in AI/ML data pipelines and analytics infrastructure
• Familiarity with geospatial, signals, or intelligence data systems
• Certification in cloud architecture or data management (e.g., AWS Certified Solutions Architect, DAMA-CDMP)
• Experience with high-performance computing (HPC)
• Experience with Infrastructure as-Code practices
• Proficiency in SPARQL query language
• Strong familiarity with implementation techniques used in broad array of package managers (npm, pip, etc.)
• Familiarity with applying library science principles such as data catalog curation, reference interview, and Functional Requirements for Biblographic Records (FRBR)
• Strong operational knowledge of the architecture (not practice) of the World Wide Web and its semiological distinction between resources and their representations.
• Experience in applying Basic Formal Ontology (BFO) concepts within and among existing semi-mutable infrastructure to achieve quantified value add

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