Data Access Engineer

Lawrence Berkeley National Laboratory is hiring a Data Access Engineer within the Materials Sciences division. The Materials Project at Lawrence Berkeley National Laboratory leverages supercomputers to uncover material properties and freely share computed data with a global community of more than 700,000 registered users. We are seeking a versatile Data Access Engineer (APIs & SDKs) to modernize the core “connective tissue” of our data platform.

This role focuses on developing, maintaining, and consolidating the Materials Project APIs and associated Python client libraries. The position bridges back-end data storage and front-end user applications, ensuring our large-scale data resources remain accessible, performant, and well documented for the international scientific community.

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!

At the Level 1 You will:

• Maintain and update Python APIs and Pydantic validation models; perform routine Mongo
  
  DB schema and query updates under general instruction.
• Maintain Python client libraries (mp-api, mpcontribs-client); troubleshoot automated CI/CD pipelines (Git Hub Actions) and monitor releases on PyPI.
• Update technical documentation (MkDocs) and provide first-line technical support for programmatic data access issues.
• Monitor API health and latency via Datadog; report and track system anomalies.
• Participate in weekly engineering sprints and contribute to shared code reviews.

At the Level 2, Includes all Level 1 responsibilities, plus:

• Architect the consolidation of disparate services; design backend logic to serve hybrid data from Mongo
  
  DB and AWS S3; independently optimize complex, high-volume queries for performance and scalability.
• Design programmatic interfaces for the Python SDKs; lead versioning and distribution strategies; implement advanced client-side logic for authentication and caching.
• Author comprehensive developer tutorials and synthesize community feedback into formal technical specifications for new API features.
• Design custom observability metrics; lead root-cause analysis for service interruptions and remediate architectural bottlenecks.
• Determine methods for new assignments and coordinate technical activities for special projects.

We are looking for:

Level 1 (C70.1)

• Bachelor’s degree in relevant field and a minimum of 2 years of related experience; or equivalent work experience.
• Demonstrated work experience in a scientific environment.
• Strong proficiency in object-oriented programming with Python.
• Demonstrated experience building or consuming RESTful APIs.
• Proficiency with Git and collaborative development on Git Hub.
• Familiarity with No
  
  SQL databases, specifically Mongo
  
  DB.
• Ability to communicate technical concepts clearly through written documentation and oral presentations.

In addition to Level 1, Level 2 (C70.2) includes:

• Bachelor’s degree with 5 years of related experience; or Master’s degree with 3 years of related experience; or equivalent work experience.
• Advanced experience in the Level 1 knowledge, skills and abilities requirements to work independently and solve problems of diverse scope.

Desired skills/knowledge:

• Advanced degree with one year of experience.
• Demonstrated work experience in computational science/research
• Experience with modern Python web frameworks (FastAPI, Starlette, or Pydantic).
• Experience with AWS cloud services, specifically S3 and Boto
  3.
• Knowledge of Python packaging and distribution (PyPI).
• Background or passionate interest in computational materials science or high-performance computing.

Additional information:

• Application date: Priority consideration will be given to candidates who apply by February 27, 2026. Applications will be accepted until the job posting is removed.
• Appointment type: This is a full-time 1 year, term appointment with the possibility of extension or conversion to Career appointment based upon satisfactory job performance, continuing availability of funds and ongoing operational needs.
• Salary range:
  • The expected…