Senior Scientific Data Engineer; Joint Genome Institute

Berkeley Lab's (LBNL) Joint Genome Institute (JGI) has an opening for a Senior Scientific Data Engineer to join the Advanced Analysis Team!

JGI has a long history of generating world‑class genomic data to address pressing national energy and environmental security challenges. Building on this expertise, JGI is now helping to define the data foundation for an emerging era of AI‑enabled scientific discovery in support of the Genesis Mission. The Advanced Analysis team at JGI builds the core data infrastructure, advanced bioinformatics workflows, and ML/AI data pipelines needed to prepare genomic data for new AI‑enabled capabilities.

We are looking for a Senior Scientific Data Engineer to help build out the systems and platforms that JGI will rely on to meet the scale, complexity, and urgency of data‑driven science.

This is an exciting and unique opportunity to apply your technical expertise in developing some of the core scientific data systems that support JGI operations, genomic data workflows, and AI capabilities. You will be asked to contribute to the design, implementation, and operations of those systems across data management, job orchestration, and platform integration projects. You will work with a highly interdisciplinary team on complex technical challenges and help drive to improve the reliability, scalability, interoperability, and maintainability of JGI's core data systems.

This position has an anticipated start date of July 1, 2026.

• Develop and enhance JGI's core scientific data and compute capabilities as part of a talented engineering team.
• Design, build, implement, and deploy production automated systems, APIs, and workflows supporting genomic data movement, metadata management, job orchestration, data access, and large‑scale scientific computing.
• Identify and resolve technical issues and integration gaps while driving continuous system improvements.
• Strengthen the reliability, scalability, observability, interoperability, and maintainability of shared production data systems while supporting sustainable operations and delivery.
• Support strong engineering best‑practices through technical reviews, knowledge sharing, and team process optimization.

• A Bachelor's Degree (or equivalent knowledge/training) in Computer Science or a related field and a minimum of 8 years of related professional experience developing, integrating, deploying, and operating production software and data systems that support metadata management, workflow orchestration, data lifecycle operations, and broad user data access or an equivalent combination of education and professional experience.
• Strong knowledge of software and data engineering fundamentals relevant to data‑intensive distributed systems, including system design, concurrency, performance, and testing.
• Experience working with database and data storage technologies including relational databases, object storage, and systems for managing structured, semi‑structured, and large‑scale data.
• Experience with data engineering and event‑driven technologies such as Airflow or Kafka.
• Experience effectively using AI coding agents such as Claude Code, Codex, Cursor, including demonstrated judgment in reviewing and validating generated software for correctness, quality, security, maintainability, and suitability for production use.
• Proficiency in Python and experience with one or more additional programming languages.
• Excellent communication skills, including experience organizing and presenting complex technical information to internal teams and stakeholders.
• Demonstrated ability to work effectively with users, stakeholders, and engineering teams to deliver technical results in a complex, interdisciplinary environment.

• A Master's Degree (or equivalent knowledge/training) in Computer Science or a related field.
• Experience working with genomics, bioinformatics, and/or next‑generation sequencing data.
• Experience with scientific workflow languages or workflow systems such as WDL and Nextflow.
• Experience with full‑stack or front‑end application development.
• Experience working in High Performance Computing (HPC) environments.