Software Engineers - Codemap services/FHIR-to-OMOP

(ID: 2024-6918)

Axle is a bioscience and information technology company that offers advancements in translational research, biomedical informatics, and data science applications to research centers and healthcare organizations nationally and abroad. With experts in biomedical science, software engineering, and program management, we focus on developing and applying research tools and techniques to empower decision-making and accelerate research discoveries. We work with some of the top research organizations and facilities in the country including multiple institutes at the National Institutes of Health (NIH).

Axle is seeking a highly ambitious, adaptable, structured, and detail-oriented Software Engineers - Codemap services/FHIR-to-OMOP to join our vibrant team at the National Institutes of Health (NIH), National center for Advancing Translational Sciences (NCATS).

Benefits We Offer:

• 100% Medical, Dental & Vision Coverage for Employees
• Paid Time Off and Paid Holidays
• 401K match up to 5%
• Educational Benefits for Career Growth
• Employee Referral Bonus
• Flexible Spending Accounts:
  • Healthcare (FSA)
  • Parking Reimbursement Account (PRK)
  • Dependent Care Assistant Program (DCAP)
  • Transportation Reimbursement Account (TRN)

We are seeking a talented Software Engineer to join our team to support projects at the NIH’s National Center for Advancing Translational Sciences (NCATS). The Software Engineer will lead the development of a Python library aimed at operationalizing semantic mappings between common data models (CDMs) such as FHIR US Core, OMOP, PCORNet, and Sentinel. This project will focus on generating ETL code targeting various platforms and systems, including SQL, Apache Spark, and Pandas DataFrames. The successful candidate will play a critical role in facilitating the integration of healthcare data across systems, ensuring interoperability, and enhancing data utility for research and clinical applications.

The ideal candidate for the Software Engineer role is a highly motivated professional with a deep understanding of healthcare data interoperability and extensive experience in developing scalable software solutions. They are proficient in Python and have a strong background in data engineering, particularly in building ETL pipelines and working with large, complex datasets. The ideal candidate is adept at navigating multiple data models, including FHIR, OMOP, and others, and has a proven ability to translate semantic mappings into executable code for diverse platforms such as SQL, PySpark, and Pandas. They thrive in collaborative environments, working closely with subject matter experts and cross-functional teams to ensure seamless data integration and transformation. This individual is detail-oriented, with a passion for creating robust, efficient, and secure software that enhances healthcare data interoperability, and they possess excellent communication skills to articulate technical concepts to both technical and non-technical stakeholders. Experience with cloud platforms and familiarity with healthcare data standards are highly desirable, as is a commitment to driving innovation in biomedical informatics and a solid understanding of healthcare data privacy and security regulations.

Responsibilities

• Lead the design and development of a Python library that ingests machine-readable semantic mappings between FHIR US Core, OMOP, and other CDMs, producing ETL code targeting multiple systems and data platforms.
• Generate executable ETL scripts for SQL, PySpark DataFrames, and Pandas DataFrames based on the semantic mappings.
• Collaborate with subject matter experts (SMEs) to refine and validate mappings between different healthcare data models, including FHIR, OMOP, and other CDMs as required by the project.
• Develop APIs to integrate the generated ETL code into external platforms and services, ensuring the automated conversion of datasets across various environments.
• Work closely with ETL development teams to ensure that the mappings and transformations are accurately implemented and optimized for performance on target systems.
• Maintain the codebase to ensure scalability, modularity, and ease of integration with different platforms and data sources.<