Senior Data Engineer (Contract)

Organization: Berkeley Earth

Location: Remote

Expected Contract Duration: 3–6 months (20-30 hours per week, variable). Extension dependent on performance.

Reports to: Executive Director

About Berkeley Earth

Berkeley Earth is a California-based nonprofit research organization producing trusted, open-access climate datasets and analysis. Our work informs policy, crucial climate research, and the public, and is widely cited by media and scientific literature. We combine rigorous methodology with robust engineering to make climate and environmental data accessible and reliable at both global and local scales.

About the Role

We are seeking a Senior Climate Data Scientist for a project-based contract role to help support the development of Berkeley Earth’s current product pipeline. This role will be responsible for the end-to-end management, improvement, and implementation of Berkeley Earth’s data pipelines, serving as the bridge between our Chief Scientist and engineering team to translate methodology into operational products for our end-users and clients.

As much of our data processing is currently done in MATLAB, this role will need to have familiarity with reading and optimizing complex scientific code in this language. Experience with Python, Linux, Google Cloud Services, Git, and best practices for structured scientific programming is also beneficial.

Responsibilities

• Transform research-grade methods into maintainable, documented workflows the engineering team can run and extend.
• Interpret and extend MATLAB workflows, understanding both the statistical logic and implementation details, not just the outputs.
• For our current climate model downscaling project, execute the agreed methodology for integrating, bias-correcting, and summarizing multi-model climate projections.
• Work closely with the engineering team to codify complex methodologies into clear, version-controlled documentation, and implement optimizations for efficiency and maintainability.
• Create structured handoffs with engineering, documentation, and reproducibility standards so engineers can confidently maintain datasets once processed.
• Operationalize and maintain pipelines, containerize code, implement automated testing, and integrate into CI/CD for reproducible builds.
• Produce versioned datasets, metadata, changelogs, and user-facing technical notes.
• Develop tailored data subsets, transformations, and derivative products to meet specialized partner and client requirements when requested, maintaining fidelity to the core scientific methodology.
• Engage with clients and end-users as needed to gather technical requirements, address data interpretation questions, and iteratively refine outputs to align with specific use-case needs.
• Perform performance monitoring as needed, troubleshooting, and enhancement of Berkeley Earth’s existing climate data pipelines, ensuring stability, scalability, and reproducibility.

Expected deliverables will include:

• Deliver reproducible, documented, public-ready datasets with complete metadata, changelogs, and scientific methodology notes.
• Refine methodology and outputs based on validation and stakeholder review.
• Implement download endpoint/API for data outputs.
• Implement robust and routine data exports to support public-facing web applications and support external users
• Deliver an engineering handoff package with version-controlled methodology documentation, code comments, and reproducibility scripts.
• Develop client-specific derivative product or data subset when required in response to technical partner requirements, ensuring methodological fidelity.
• Perform baseline performance benchmarking and maintenance documentation for all pipelines modified or created during the contract term.

Qualifications

Required

• Advanced climate science/statistics expertise with a focus on climate model outputs (CMIP, CORDEX, or similar).
• Proficiency with MATLAB: able to read, extend, and optimize complex scientific code.
• Proven ability to translate research code into production pipelines.
• Strong Python skills for orchestration, data delivery, and integration with cloud-based systems.
• Demonstrated ability to optimize code performance in big data contexts.
• Experience with reproducibility: CI/CD, containerization, automated QA.

Preferred

• Familiarity with bias correction, downscaling, uncertainty quantification, and ensemble synthesis.
• Experience translating scientific data into useful real-world applications.
• Familiarity with common statistical techniques and metrics
• API or data service development experience.
• Familiarity with Google Cloud Services
• Geospatial tooling (GDAL, Rasterio) and handling large gridded datasets.

Location

Contract Extension

Contract extension and/or the possible conversion to full-time status will be dependent on performance during the initial contract period.

To Apply

Please send CV and cover letter to admin@berkeleyearth.org. Applications submitted without a cover letter will not be considered.