Jobs in Rockville, MD

About the role

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.

What you'll bring

• Education & Background: Bachelor’s degree in Computer Science, Data Science, Bioinformatics, Biomedical Informatics, Information Systems, Engineering, or a related field, or equivalent practical experience.
• Proven experience as a Data Engineer, Analytics Engineer, Data Integration Developer, Bioinformatics Engineer, or similar data-intensive role
• Data Engineering Expertise: Strong proficiency in Python and SQL for data manipulation, transformation, scripting, automation, and analysis.
• Hands-on experience building ETL/ELT processes and data pipelines to support large, complex, multi-source datasets.
• Familiarity with scalable data processing approaches, including Spark/ PySpark or similar frameworks, for high-volume or complex transformations is required.
• Analytical Skills: Solid understanding of data modeling, relational databases, data warehouses, data lakes, metadata, and database concepts.
• Ability to work with complex, multi-modal datasets, including structured, semi-structured, and unstructured data, and optimize data workflows for reliability, performance, usability, and long-term maintainability.
• Best Practices: Knowledge of software engineering and data engineering best practices, including version control using Git, code review, automated testing, documentation, peer review, and change management.
• Experience ensuring data quality and using lineage, provenance tracking, audit trails, or documentation practices to support transparency, reproducibility, and data flow traceability.
• Collaboration & Communication: Excellent problem-solving skills and the ability to communicate effectively with both technical and non-technical stakeholders.
• Comfortable working in an interdisciplinary environment with biomedical researchers, analysts, developers, and project teams.
• Capable of translating domain-specific needs into technical solutions and explaining technical risks, limitations, and dependencies in clear stakeholder-focused language.

Benefits