Biomedical informatics platform for clinical research and health data integration
Digital Infuzion operates at the intersection of healthcare IT and clinical research, built on FHIR/HL7 standards with a modern data stack (Python, PySpark, Airflow, Redshift, OpenSearch). The hiring mix—engineering and research roles equally weighted, with senior and director-level leadership gaps—reflects an organization scaling clinical operations alongside infrastructure. Active projects span federal multi-cloud platforms, clinical trial recruitment modeling, and NLP biomedical mining, while pain points cluster around federal compliance, data governance, and trial recruitment diversity.
Notable leadership hires: Clinical Research Director, Technical Lead
Digital Infuzion is a software and healthcare IT company serving health systems, research institutions, and medical professionals. Founded in 1999 and based in Rockville, Maryland, the 51–200-person organization specializes in biomedical informatics, real-world data services, research IT support, and digital surveillance capabilities. The platform integrates clinical and research data via HL7/FHIR standards, processes it through AWS and Azure infrastructure with PySpark and Airflow orchestration, and surfaces insights through tools like Redshift and Cognos. The company operates across federal research compliance workflows, clinical trial management, and data linkage services—domains where regulatory rigor and data integrity are foundational.
Core infrastructure: AWS (Glue, Lambda, Step Functions), Azure, Python, PySpark, Apache Airflow. Data layer: Redshift, DynamoDB, MongoDB, Parquet, OpenSearch. Standards: FHIR, HL7. Analytics: Cognos. Collaboration: Jira, Confluence.
Active initiatives include federal multi-cloud data platforms, clinical trial recruitment modeling, NLP biomedical literature mining, privacy-preserving record linkage, and clinical research support programs. Projects address clinical trial diversity, federal data linkage, and DSMB/OSMB operations.
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Digital Infuzion's technology stack, projects, and hiring signals are inferred from public hiring and company data — career pages, public listings, and company web presence — then clustered and de-duplicated. Figures are estimates that refresh over time. Read our full methodology →
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