Data Engineer

Responsibilities

• Required Qualifications

Benefits

Additional Information

(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.

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