Data Systems Software Engineer

Lawrence Berkeley National Laboratory•Berkeley, CA

11h•Hybrid

About The Position

Lawrence Berkeley National Laboratory is hiring a Data Systems Software Engineer within the Scientific Data division. In this exciting role, you will work with researchers and application scientists from the DOE Office of Science community, and faculty and students from universities both domestically and abroad, on a wide array of software development and data science issues serving the broader SciData mission. We’re here for the same mission, to bring science solutions to the world. Join our team and YOU will play a supporting role in our goal to address global challenges! Have a high level of impact and work for an organization associated with 17 Nobel Prizes! Why join Berkeley Lab? We invest in our employees by offering a total rewards package you can count on: Exceptional health and retirement benefits, including pension or 401K-style plans A culture where you’ll belong - we are invested in our teams! In addition to accruing vacation and sick time, we also have a Winter Holiday Shutdown every year. Parental bonding leave (for both mothers and fathers) Pet insurance

Requirements

Bachelor's degree and 5 years of related experience, or 3 years and a Master's degree, or three years and a PhD degree, or an equivalent combination of education and work experience.
Familiarity with command-line and system administration tools in UNIX-based operating systems like Linux or MacOS.
Proficiency in Python.
Proficiency in multiple general-purpose and/or domain specific programming languages such as JavaScript, Typescript, C/C++, Java, MATLAB, R, etc.
Familiarity with current major data storage, data management, and data analysis methodologies, tools, and frameworks, such as "data lakehouse" architectures.
Experience and expertise with AI tools and frameworks, including those for agentic workflows.
Familiarity and some experience with AI and related technologies to develop, document, test, and deploy software
Excellent English written and oral communication.
Strong interpersonal skills for working in a diverse team environment.
Ability to obtain security clearance sufficient to interact with CUI and/or Classified information.
Bachelor’s degree and 8 years of related experience, or 6 years and a Master’s degree, or three years and a PhD degree, or an equivalent combination of education and work experience.
Demonstrated experience with the entire software development process, from requirements through design, to implementation, release and deployment.
Experience and expertise with current major data storage, data management, and data analysis methodologies, tools, and frameworks, such as "data lakehouse" architectures
Experience with AI tools and frameworks, including those for agentic workflows.

Nice To Haves

Experience and expertise with cybersecurity theory and practice.
Domain expertise in chemical engineering, chemistry, physics, or a related field.
Deep understanding of the software development lifecycle.
Understanding of HPC and large-scale systems.
Familiarity with orchestration platforms (kubernetes), OS systems and tools, parallel programming, databases, data management, resource management.
Ability to troubleshoot and solve problems of diverse scope where analysis of data requires evaluation of identifiable factors.
Ability to network with senior internal and external personnel in their own area of expertise.
Experience with software project management and system administration.
Experience leading cross-functional teams.
Experience serving as a subject matter expert in cybersecurity practices for scientific computing, conducting security reviews, and establishing organizational standards for secure software development and data handling.
Experience identifying and securing new collaborative opportunities and resources.
Demonstrated ability to work effectively as part of a cross-disciplinary team.
Ability to resolve complex issues in creative and effective ways.
Ability to exercise judgment in selecting methods, techniques and evaluation criteria for obtaining results.
Ability to network and collaborate with key contacts outside their own area of expertise.

Responsibilities

Apply modern data management practices and tools to scientific data challenges, using current best-practices in database architectures, storage formats, query languages, and metadata standards.
Build software tools to perform complex data engineering, analysis, and curation tasks for both long- and short-term needs using best-in-class algorithms, methodologies, and/or practices.
Apply and follow current and effective cybersecurity practices for systems administration, data management, software development, and communications.
Use and adapt AI (and ML) tools and practices for both the software development lifecycle and as part of delivered functionality to meet both current and future requirements of scientific teams and projects.
Collaborate and communicate effectively within cross-functional teams including domain scientists, facility staff, and computer scientists and engineers.
Create tests and software documentation (both developer and user-focused).
Optimize, debug, and maintain software once it is deployed into production.
Employ software development lifecycle, devops and release management practices.
Collaborate with other developers through modern tools and practices.
Network with senior internal and external personnel in their own area of expertise.
Work on and resolve problems of diverse scope where analysis of data requires evaluation of identifiable factors.
Demonstrate good judgment in selecting methods and techniques for obtaining solutions.
Coordinate and/or lead software engineering and science teams with defining requirements and features for software systems.
Architect and implement division-wide or cross-project data management tools, methods, or strategies to optimize data integrity, access, and scale.
Lead the design and development of major software systems or components, setting the technical direction and ensuring the integration of best-in-class algorithms and methodologies across multiple projects.
Strategically evaluate, pioneer, and integrate novel AI/ML tools and agentic computing practices to deliver transformative capabilities, addressing complex, future-looking scientific requirements.
Champion and evolve the group's software engineering standards, including testing, documentation, deployment, and operations.
Mentor junior staff and developers, and proactively establish and nurture strategic partnerships with internal and external research teams to advance collaborative project goals.
Establish and maintain relationships with stakeholders in the external scientific computing community.
Present to audiences within and outside the lab.
Work at a higher level of independence when completing assignments.
Work on and resolve complex issues where analysis of situations or data requires an in-depth evaluation of variable factors.
Exercise judgment in selecting methods, techniques and evaluation criteria for obtaining results.
Determine methods and procedures on new assignments and may coordinate activities of other personnel.
Network with key contacts outside your own area of expertise.

Benefits

Exceptional health and retirement benefits, including pension or 401K-style plans
A culture where you’ll belong - we are invested in our teams!
In addition to accruing vacation and sick time, we also have a Winter Holiday Shutdown every year.
Parental bonding leave (for both mothers and fathers)
Pet insurance

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