Senior Scientific Data Engineer

Lawrence Berkeley National Laboratory's Joint Genome Institute is seeking a Senior Scientific Data Engineer to help design and sustain the data platforms that underpin genomic data generation, metadata management, and laboratory operations. This hybrid role in the San Francisco Bay Area offers the opportunity to influence systems that span LMS/LIMS, data warehouse and lakehouse architectures, and project management workflows, with the possibility to lead major technical initiatives across diverse teams.

Responsibilities

• Translate intricate scientific, operational, and user needs into concrete specifications, architecture, and implementation plans for system enhancements, integrations, and shared data platforms.
• Design, develop, deploy, and support core systems, APIs, and workflows including the Laboratory Information Management System (LMS/LIMS), Data Warehouse/Data Lakehouse, and Proposal/Project Management platforms to enable genomic data generation, metadata management, and laboratory operations.
• Lead the resolution of complex technical challenges, drive system improvements, and ensure production platforms are reliable, scalable, interoperable, and high-performing.
• Advocate engineering best practices through technical reviews, documentation, mentorship, and ongoing refinement of development and operational processes.

Requirements

• A Bachelor’s degree in Computer Science or a related field with a minimum of 8 years of professional experience developing, integrating, deploying, and supporting production software applications and data systems that enable metadata management, workflow orchestration, data lifecycle operations, and broad user access to scientific and operational data.
• Experience with data engineering and event-driven technologies such as Airflow or Kafka (or equivalent).
• Hands-on experience with relational databases, object storage, and systems supporting structured, semi-structured, and large-scale datasets.
• Solid grounding in software and data engineering principles for large-scale production systems, including system design, APIs, testing, concurrency, reliability, scalability, interoperability, and performance optimization.
• Proficiency in Python and experience with one or more additional programming languages.
• Experience using AI-assisted development tools with sound judgment to evaluate generated code for production readiness.
• Ability to provide technical leadership shaping system architecture and direction across cross-functional engineering teams.
• Excellent communication skills, including the ability to present complex technical information to internal teams and stakeholders.
• Demonstrated experience collaborating with stakeholders to understand project goals and translate them into automated systems, technical specifications, and implementation plans.

Technologies

• Python
• Airflow
• Kafka
• Laboratory Information Management System (LMS/LIMS)
• Data Warehouse/Data Lakehouse
• AI-assisted development tools

Benefits

• Exceptional health benefits
• Generous paid time off, sick time off, and holidays
• A culture where you’ll belong, with investment in our teams
• Relocation assistance
• Hybrid work schedule eligibility

Why join Berkeley Lab?

• Strong health benefits
• Generous paid time off, sick leave, and holidays
• Inclusive culture with support for teams

Additional Information

• Application deadline: Priority consideration for applications with resume and cover letter by June 22, 2026; applications accepted until the posting is removed.
• Appointment type: Full-time, exempt from overtime pay, monthly paid, two-year term with benefits eligibility, with potential extension or conversion to a Career appointment based on performance, funding, and operational needs.
• Salary range: USD 139,440 - 174,312 annually, within the broader job code range; final salary determined by qualifications, experience, and alignment with peers.
• Background check: A background check is required; convictions will be evaluated for relevance to responsibilities; a history does not automatically disqualify.
• Work modality: Hybrid schedule with on-site work at Lawrence Berkeley National Laboratory, 1 Cyclotron Road, Berkeley, CA 94720; must reside within 150 miles; rare cases of full remote work may be considered; Real ID or other acceptable identification required for access.
• Relocation assistance: Eligible
• Work authorization: Must be legally authorized to work in the United States; Berkeley Lab does not provide visa sponsorship for this position.