Scientific Data Systems Engineer
About Carbon Mapper
Carbon Mapper is a non-profit organization based in Pasadena, CA with the mission to drive greenhouse gas emission reductions by making methane and carbon dioxide data accessible and actionable. We leverage remote sensing technology to detect, pinpoint, and quantify methane and carbon dioxide (CO2) emissions at the scale of individual facilities. All of our methane and CO2 data is made publicly available for non-commercial use on our Carbon Mapper Data Portal to provide decisionmakers with the information they need to prioritize and take mitigation action.
Carbon Mapper also works with stakeholders and decision makers to fill data gaps, lead on cutting edge science, collaborate to drive reductions, and advance education and insights on emissions globally. To do this, we work with partners to leverage a constellation of satellites. Data from these satellites will offer the next major step in scaling up the organization's robust data portal featuring thousands of direct observations of global methane and CO2 super-emitters.
To learn more about Carbon Mapper, please visit us at https://carbonmapper.org.
To view our data, please visit us at https://data.carbonmapper.org.
About The Role
Carbon Mapper is seeking a data generalist to help support and improve the usability, discoverability, and reliability of Carbon Mapper’s data ecosystem end-to-end. This role operates at the intersection of science, engineering, and communications, and involves developing a strong understanding of the Carbon Mapper data catalog in order to help users locate, interpret, and troubleshoot datasets across raster, vector, remote-sensing, modeled, and machine-learning-derived products.
Responsibilities include identifying catalog issues, inconsistencies, and usability gaps; contributing to the development of clear nomenclature, metadata standards, product guides, and user documentation; and supporting data reprocessing efforts driven by science team requests, algorithm updates, and quality assessments.
This role includes hands-on work with Python, geospatial and scientific data libraries, and complex SQL queries against relational databases. The position also supports the design and monitoring of data pipelines and dashboards, helping ensure production data and ML-derived products are reliable, reproducible, versioned, and observable. Additional responsibilities include contributing to catalog feature development (such as search, browsing, and visualization), creating example notebooks and user resources, and participating in cross-functional planning and working sessions with science, engineering, and communications teams.
Essential Duties and Responsibilities
· Develop and maintain a working understanding of Carbon Mapper’s data catalog (including Tanager, AVIRIS-3, AVIRIS-NG, GAO, EMIT, modeled products, machine-learning-derived products, and plume attribution datasets) in order to help locate, interpret, and explain datasets.
· Support reproducibility, versioning, provenance tracking, and observability of machine-learning- and algorithm-derived data products in production, in coordination with algorithm owners.
· Execute and support data reprocessing workflows driven by science team requests, data quality findings, and evolving processing logic, in collaboration with science and engineering teams.
· Identify, document, and help resolve data quality issues, inconsistencies, naming challenges, and usability gaps across the data catalog.
· Contribute to the development of consistent nomenclature, metadata standards, product versioning practices, and user-facing documentation (such as a data handbook, product guides, and release notes).
· Build and maintain internal dashboards to monitor pipeline health, model and algorithm status, reprocessing progress, catalog usage metrics, and data quality indicators.
· Contribute to the design and prioritization of future catalog features.
· Write clear, maintainable Python code using geospatial, scientific, and machine learning libraries, and develop complex SQL/PostGIS queries against the data warehouse.
· Develop and maintain example notebooks, quick-start tutorials, and reproducible workflows to support use of both raw and machine-learning-derived data products.
· Collaborate across science, engineering, and communications/outreach teams through meetings, planning sessions, and roadmap discussions.
Minimum Qualifications (Knowledge, Skills, and Abilities)
Must-Have Skills & Experience:
● Experience with Python-based data engineering in scientific or geospatial environments, including working with large and evolving datasets.
● Experience with GIS concepts and formats (for example raster and vector data, GeoTIFF/COG, NetCDF, Zarr, Parquet, and STAC) and remote-sensing data products.
● Experience writing complex SQL queries and modeling data in relational databases; experience with PostGIS is preferred.
● Experience supporting data reprocessing workflows driven by algorithm updates, scientific validation, or data quality findings, with attention to reproducibility, versioning, and provenance.
● Experience supporting machine-learning- or algorithm-derived data products in production environments, including algorithm lifecycle management, change tracking, and operational monitoring.
● Experience working in cloud-based data environments (AWS preferred), including storage, compute, and data access patterns.
● Experience improving the usability, reliability, or accessibility of scientific or technical datasets for collaborators or end users.
Nice-to-Have Skills:
· Experience with cloud-native geospatial tools and workflows (for example Planetary Computer, Kerchunk, and Intake catalogs).
· Experience working with machine-learning or process-based atmospheric models in production or operational environments.
· Contributions to open-source geospatial or Python projects.
Hours
This is a full-time, exempt position (40 hours per week). Occasional after-hours and weekend work may be required to meet deadlines. This role also participates in a compensated on-call rotation, typically not exceeding one week per month.
Location
Carbon Mapper is headquartered in Pasadena, California, but we embrace the virtual office and are continuing to grow our team across the United States.
Compensation
The total compensation for this opportunity includes a base salary range of $165,000 - $185,000/year. This is our target compensation range and is subject to multiple factors including level, experience, and location. As you go through our interview process, our recruiter will work with you to identify a competitive base salary within the proposed range.
