Data Engineer

(ID: 2026-2532) 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). 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 Data Engineer to support biomedical science, clinical research data integration, and advanced data analysis initiatives. In this role, you will design, build, optimize, and maintain data pipelines and data workflows that support the ingestion, transformation, harmonization, validation, and delivery of complex biomedical datasets. You will collaborate closely with scientists, researchers, data scientists, bioinformaticians, application developers, and technical stakeholders to ensure data is accessible, well-structured, secure, documented, and reusable for biomedical research, analytics, reporting, and discovery. The ideal candidate will have strong experience with Python, SQL, ETL/ELT development, data modeling, data quality practices, and research data lifecycle support. This role requires the ability to work with complex multi-source datasets, support analytics and application-facing data products, and contribute to scalable, well-governed data solutions that align with the Data Science Client Services branch priorities for data accessibility, interoperability, reproducibility, modernization, and secure research enablement. Key Responsibilities Data Pipeline Development: Design, build, test, and maintain data pipelines to ingest, transform, harmonize, and integrate diverse biomedical and research data sources, including clinical, genomic, experimental, imaging, biospecimen, operational, and other scientific datasets. Develop reusable transformation logic and curated datasets that support analytics, reporting, dashboards, applications, APIs, and downstream research workflows. Data Integration and Lifecycle Support: Support the full research data lifecycle by enabling reliable data movement from source systems and storage environments into structured, analysis-ready formats. Assist with data ingestion, curation, metadata capture, data refreshes, source-to-target mapping, schema management, and long-term maintainability of data products and workflows. Collaboration: Work closely with data scientists, bioinformaticians, researchers, application developers, project managers, and government stakeholders to gather requirements and deliver practical data solutions. Translate scientific and operational data needs into technical specifications, data models, transformation logic, and reusable datasets that accelerate biomedical research workflows and support informed decision-making. Quality & Governance: Implement data validation checks, reconciliation routines, testing practices, and monitoring processes to ensure data accuracy, completeness, consistency, and integrity. Follow data governance and security best practices, including documentation of transformations, lineage, assumptions, access requirements, and compliance considerations related to sensitive, regulated, de-identified, or access-controlled research data. Dashboarding & Integration: Create or support interactive dashboards, reporting layers, APIs, and application-ready datasets that allow researchers an…