Data Engineer - Bioinformatics

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.   

Please include a cover letter with your application detailing your qualifications and experience as they relate to this position. 

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, focused on integration of complex biological sequence datasets from diverse sources. This includes writing production-quality Python code to parse, validate, and transform sequence data from published research papers, public databases, and experimental outputs. This role requires both technical excellence in data engineering and the ability to understand biological research contexts to ensure data integrity and scientific validity. 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, potentially mentoring junior engineers, 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 implement scalable, robust data pipelines for bioinformatics data using workflow managers (Snakemake, Nextflow, or similar) that perform data validation and quality control at every pipeline stage through tests and clear data visualization. 

• Stay up to date with scientific literature to understand data context and processing requirements. 

• Document data provenance and transformation steps comprehensively. 

• Apply statistical tools and programming languages (e.g., Python, R) to analyze large datasets, develop custom functions, and extract actionable insights through effective visualization. 

• Establish and maintain data standards, formats, workflows, and documentation to ensure data quality, accessibility, and reproducibility across projects. 

• Collaborate with interdisciplinary teams, potentially mentor junior engineers, and direct or assist in directing the work of others to meet project goals while advising stakeholders on data strategies and best practices. 

What you bring: 

• Bachelor’s degree in Computer Science, Data Science, Statistics, Applied Mathematics, or a related field with 3+ years of experience applying and customizing data mining and data analysis methods and techniques. An equivalent combination of education and relevant experience will be considered.  

• Experience with data formats such as FASTA, FASTQ, and annotation files. 

• Experience with data validation and quality control techniques. 

• Clear technical documentation and communication skills. 

• Experience in building scalable data solutions, working with big data technologies, and ensuring data quality and accessibility. 

• Expertise in utilizing data visualization libraries and software (e.g., Matplotlib, R, Jupyter notebooks). 

• Demonstrated expertise in statistical analysis. 

• 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.