Senior Data Architect

 

Axle is seeking a Senior Data Architect to join our team supporting the National Center for Advancing Translational Sciences (NCATS), located in Rockville, MD.

 

About the Mission

Join the team powering the National COVID Cohort Collaborative (N3C) — now expanding into the National Clinical Cohort Collaborative, the largest harmonized clinical data resource in the United States. N3C integrates diverse, de-identified EHR, claims, registry, and public health data to accelerate discovery and translational research across diseases.

This is not a traditional engineering role. It’s a chance to define how clinical data is represented, harmonized, and made research-ready for thousands of investigators. As a senior architect and informatics leader, you will shape national data standards, ensure semantic interoperability, and help guide the future of data-driven biomedical research.

 

The Opportunity: Your Impact

As a Senior Data Architect, you will lead the design and governance of the data architecture that underpins one of the most ambitious biomedical data resources in existence. You’ll ensure that diverse clinical, administrative, and external datasets are accurately modeled, semantically consistent, and analytically usable across multiple domains.

You will collaborate closely with informaticians, data scientists, and data engineers to ensure data are FAIR (Findable, Accessible, Interoperable, and Reusable) and aligned with national data model initiatives.

 

What You’ll Do

Architect and Evolve the National Clinical Data Model

• Lead the design and optimization of scalable data models across diverse healthcare domains.
• Extend and refine OMOP and FHIR vocabularies for evolving data types including genomics, imaging, and environmental data.
• Define canonical representations of key concepts (diagnoses, labs, medications, encounters, outcomes) to ensure semantic integrity across sources.
  
   

Advance Data Interoperability and Harmonization

• Oversee cross-model translation between OMOP, PCORNet, TriNetX, ACT, and FHIR.
• Govern terminological consistency using SNOMED CT, LOINC, ICD, RxNorm, CPT, and NDC vocabularies.
• Implement curation pipelines that align heterogeneous data into harmonized, analysis-ready structures.
  
   

Enable Federated and Privacy-Preserving Research

• Support linkage of de-identified records across clinical systems, registries, and claims datasets.
• Guide the implementation of privacy-preserving record linkage (PPRL) and federated learning frameworks.
• Collaborate with governance teams to ensure compliance with HIPAA, FISMA, and NIH data-sharing policies.
  
   

Champion Data Quality and Provenance

• Develop frameworks and dashboards for assessing data completeness, consistency, and validity across contributing sites.
• Define and track metadata standards to ensure reproducibility and transparency.
  
   

Provide Strategic Leadership

• Mentor data scientists and engineers in informatics best practices and semantic data design.
• Serve as a liaison to standards development organizations (OHDSI, HL7, NCATS CD2H, etc.).
   

What You’ll Bring (Required Qualifications)

• Master’s or Doctoral degree in Biomedical Informatics, Health Information Science, Computer Science, or a related field.
• 6+ years of experience in healthcare data architecture, data integration, or clinical informatics.
• Deep expertise in EHR data, clinical terminologies, and interoperability standards.
  Demonstrated depth of experience working with OMOP, FHIR, or other Common Data Models (CDMs) at scale.
• Proficiency in SQL and Python along with collaborative experience with engineers on data transformation workflows.
• Strong understanding of healthcare data sources: EHRs, claims, registries, and observational cohorts.
  Familiarity with data quality frameworks, metadata management, and data governance principles.
• Proven ability to communicate technical data concepts to scientific and clinical audiences.
   

Preferred Qualifications

• Experience architecting or managing large-scale, multi-institutional research data repositories.
• Working knowledge of cloud platforms (AWS, GCP, or Azure) and modern data architectures (e.g., data lakes, knowledge graphs).
• Experience with workflow orchestration tools like Airflow.
• Understanding of federated data systems and distributed query infrastructure.
• Contributions to open-source healthcare informatics projects (e.g., OHDSI, HL7).