The Pacific Northwest National Laboratory (PNNL) and the Environmental Molecular Sciences Laboratory (EMSL) seek a hands-on engineer to focus on Linux DevOps, Kubernetes (K8s) cluster management and data management of complex, high-throughput biological and environmental data. The EMSL is a U.S. Department of Energy (DOE) Office of Science user facility that provides innovative and breakthrough experimental and computational science that addresses DOE Office of Biological and Environmental Research (BER) programs by providing access to more than 75 state-of-the-art instrumental and high-performance computing capabilities. EMSL users address some of the most important molecular-to-mesoscale challenges relevant to DOE missions. The position requires an ability and willingness to assist EMSL staff and users in understanding and adhering to the EMSL data management policies and procedures.
The candidate should have experience in Linux DevOps, on-premises Kubernetes cluster management, Linux system administration, data workflows, and modern software engineering methodologies. The candidate is expected to work closely with EMSL’s Computing Platforms team to administer Kubernetes resources and develop robust data workflow automation processes and back-end data storage systems that support data sharing across DOE facilities and the broader scientific community.
- Perform DevOps and system administration of Linux servers, Linux-based HPC systems and on-premises Kubernetes clusters.
- Develop and maintain data management and processing workflows.
- Established local reputation with specialization in at least one S&E domain. Making key contributions in setting technical direction.
- Developing and optimizing capabilities at the division level. Developing external reputation. Building effective project teams with membership across a group, S&E domain, and/or directorate. Contributing to the local organization through mentoring junior staff and taking on operational assignments.
- Selects and develops technical approaches on assignments with occasional oversight on complex problems. Principal investigator or co-PI on projects or tasks while integrating capabilities of work team members. Supports scoping, scheduling, and budgeting at a project or major task level. Generates new ideas for proposals and business development opportunities while leading the development of the technical section of small to medium proposals.
- Establishing leadership roles in professional communities, including professional societies, other laboratories, academia, and industry. The lead of technical products.
Discipline, principal job duties/expectations, and qualitative and quantitative measures of performance that exceed the Functional Descriptor:
- Demonstrates leadership in developing the strategy and technical objectives for data management in EMSL.
- Conceives, plans, and executes technical approaches for software development for EMSL data management.
- Maintain resource capabilities in working conditions for EMSL user and staff use. Stay current with the state of the art and work with EMSL leadership to improve capabilities to remain at the cutting edge.
- Provide information and advice for developing capabilities and sunsetting resources that are obsolete or no longer aligned with institutional priorities.
- Provide advice and feedback on EMSL project execution (lessons learned). Provide information needed for facility reports and strategy documents (dashboard reports, workshop reports, strategy/planning documents).
- Build effective project teams with membership across a group, science & engineering domain and/or directorate.
- Serve as a role model for quality, safety, and security.
- BS/BA and 5+ years of relevant work experience -OR-
- MS/MA and 3+ years of relevant work experience -OR-
- PhD with 1+ year of relevant experience
- Demonstrated experience in modern software engineering and Linux DevOps methodologies.
- Demonstrated experience installing, configuring, upgrading, maintaining and administering on-premises Kubernetes clusters in Linux.
- Working knowledge of data management platforms, ontologies, and metadata management strategies.
- Meaningful experience with databases, containerization (docker or podman), orchestration (Kubernetes).
- Python programming expertise.
- Excellent communications, interpersonal, teamwork and leadership skills