Data Access Engineer

Lawrence Berkeley National Laboratory•Berkeley, CA

1d•$105,000 - $161,000•Hybrid

About The Position

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. This 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!

Requirements

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 GitHub.
Familiarity with NoSQL databases, specifically MongoDB.
Ability to communicate technical concepts clearly through written documentation and oral presentations.
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.

Nice To Haves

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 Boto3.
Knowledge of Python packaging and distribution (PyPI).
Background or passionate interest in computational materials science or high-performance computing.

Responsibilities

Maintain and update Python APIs and Pydantic validation models; perform routine MongoDB schema and query updates under general instruction.
Maintain Python client libraries (mp-api, mpcontribs-client); troubleshoot automated CI/CD pipelines (GitHub 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.
Architect the consolidation of disparate services; design backend logic to serve hybrid data from MongoDB 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.