Data Engineer I
Howard Hughes Medical InstituteAbout the role
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The Howard Hughes Medical Institute’s Janelia Research Campus is a pioneering research center in Ashburn, Virginia, where scientists pursue fundamental questions in the life sciences. Our integrated teams of biologists, computational scientists, and tool-builders innovate research practices and technologies to solve biology’s deepest mysteries. HHMI launched Janelia in 2006, establishing an intellectually enriching environment for scientists to do creative, collaborative, hands-on work. We share our methods, results, and tools with the scientific community.
Summary:
AI@HHMI: HHMI is investing $500 million over the next 10 years to support AI-driven projects and to embed AI systems throughout every stage of the scientific process in labs across HHMI. The AI initiative will be centered at HHMI’s Janelia Research Campus. Janelia has been at the forefront of AI-driven research in biology for more than 15 years. Its forward-thinking structure, centralized funding, and collaborative culture make it ideally suited to take this bold leap forward. To learn more about the initiative, visit here.
About the role:
We're seeking a skilled Data Engineer to drive scientific innovation through robust data infrastructure. In this role, you’ll design, develop, and optimize scalable data pipelines and tools for the ingestion, transformation, and integration of large, heterogeneous datasets. Your work will directly support computational research initiatives, including machine learning and AI applications. Collaborating closely with multidisciplinary teams of computational and experimental scientists, you’ll help define and implement best practices in data engineering, ensuring data quality, accessibility, and reproducibility. You’ll also be responsible for maintaining detailed documentation and automating workflows to streamline the path from raw data to scientific insight.
What we provide:
A competitive compensation package, with comprehensive health and welfare benefits.
A supportive team environment that promotes collaboration and knowledge sharing.
The opportunity to engage with world-class researchers, software engineers and AI/ML experts, contribute to impactful science, and be part of a dynamic community committed to advancing humanity’s understanding of fundamental scientific questions.
Amenities that enhance work-life balance such as on-site childcare, free gyms, available on-campus housing, social and dining spaces, and convenient shuttle bus service to Janelia from the Washington D.C. metro area.
What you’ll do:
Design and customize data pipelines, leveraging appropriate tools, methods, and storage formats to process large structured and unstructured datasets for analysis and AI model training.
Source, consolidate, and curate data to support a range of computational research needs, ensuring reproducibility through careful documentation of code, data, and workflows.
Apply statistical and programming tools (e.g., Python, R) to analyze datasets, extract insights, and communicate findings through clear visualizations.
Establish and maintain standards for data formats, storage, and processing workflows, while continuously learning new tools and collaborating closely with interdisciplinary teams.
What you bring:
A Bachelor’s degree in Computer Science, Data Science, Statistics, Applied Mathematics or related fields and 0 to 2 years of relevant experience. An equivalent combination of education and relevant experience will be considered.
Proficiency in the use of the Linux command line, programming languages and frameworks and formats for data management (e.g., Python, R, Numpy, Pandas, HDF5).
Familiarity with high-performance computing environments and cloud storage (e.g., AWS, GoogleCloud).
Proficiency in the application of data mining and data analysis methods and techniques.
Proficiency in utilizing data visualization libraries and software (e.g., Matplotlib, R, Jupyter notebooks).
Detail-oriented, creative, and organized team player with strong communication skills and a collaborative mindset.
Able to effectively manage time, prioritize tasks, and clearly convey complex data concepts to technical and non-technical audiences.
Physical Requirement
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