Senior Data Architect

GDIT is seeking an experienced Real-World Data Architect for upcoming opportunities to support large-scale real-world data initiatives. In this role, you will be responsible for the design and evolution of secure, cloud-based data architectures that integrate multiple disparate data sources to create research-ready datasets in secure enclaves and analytics platforms. You will work closely with data linkage, PPRL, cloud architecture, enclave, and program operations teams to ensure that real-world data are modeled, governed, and delivered in ways that are scalable, policy-compliant, and aligned with emerging real-world data expectations.

• Design and maintain end-to-end RWD data architectures that leverage centralized, federated, and hybrid platforms, while honoring complex DUAs, licensing terms, and privacy constraints.
• Define and evolve canonical data models, ontologies, metadata standards, and mapping strategies for real-world data sources, including implementation and management of changes over time.
• Partner with Data Linkage and PPRL subject matter experts so that linked data sets are structured, indexed, and partitioned to support efficient, reproducible research results and analytics.
• Architect cloud-native data flows and pipelines that meet FedRAMP/FISMA Moderate expectations and Zero Trust-aligned security requirements.
• Translate DUAs, IRB and Privacy Board decisions, and data broker/licensing agreements into technical controls, including deidentification, access, retention and audit rules.
• Implement and oversee data catalog, lineage, and metadata services so investigators and partners can discover available data assets, understand providence and linkage methods, and select appropriate data for studies, trials, and other use cases.
• Collaborate with real-world data initiatives and partners to align data models, APIs, and governance approaches, ensuring interoperability and re-use of data and methods across platforms.
• Provide architectural guidance and best practices to multidisciplinary teams (IT engineers, data engineers, linkage experts, security, analysts, and scientific users) and contribute to technical documentation, training materials, and design reviews.
• Support the growth of the Fed Health division by developing and maintaining high quality relationships with customers and partners, ensuring alignment with the National Institutes of Health's strategic direction.

• Master’s degree in a relevant field or equivalent combination of education and experience.
• Minimum of 10 years of experience in data engineering, architectures, data science, clinical informatics, clinical data management, or equivalent experience working with biomedical information at scale.
• Demonstrated experience integrating health-related real-world data
  , such as claims, EHR/clinical data, registries, or commercial data, with practical familiarity with healthcare coding, harmonization, and longitudinal cohort design.
• Proven ability to interpret and implement data use constraints from DUAs, ethics and privacy reviews, and licensing agreements into technical designs, including access controls, retention, de‑identification, and export rules.
• Hands‑on experience with modern data architectures and tools
  , including batch and streaming ETL/ELT, workflow orchestration, metadata and catalog services, and scalable storage and query engines.
• Excellent communication and collaboration skills
  , with a track record of working effectively with senior leadership as well as multidisciplinary technical and scientific teams in government, research, or healthcare settings.
• Security Clearance: Able to obtain and maintain a Government Public Trust or higher.
• Location: Hybrid / Washington, DC metropolitan area preferred to support on‑site collaboration with federal customers and other partners.

• Advanced degree in a relevant field (PhD, MD, or equivalent).
• Prior experience supporting Federal health, research or related agencies on data platforms, secure enclaves, or real‑world data initiatives.
• Familiarity with healthcare interoperability and research standards (e.g.,…