Geospatial Data Engineer

Radiant Earth Foundation is looking for candidates based in either the United States, Ghana, Ivory Coast, or Senegal for this position.

Our core mission is to make insights from remote sensing data and machine learning an order of magnitude more accessible for global non-profits, humanitarian organizations, and companies and governments in emerging economies.

We do this by curating, hosting, and listing/redirecting to open training datasets through Radiant MLHub. MLHub is a repository and registry of geospatial training data, and we lead community efforts to develop standards and increase interoperability of these data for machine learning applications.

In addition to training data catalogs, we work with organizations on complex use cases with high-impact outcomes. Since our founding in 2016, we’ve worked with Omidyar Network (a founding funder), Bill and Melinda Gates Foundation (another founding funder), as well as NASA, GIZ, Digital Earth Africa, Schmidt Futures, McGovern Foundation, and more.

We are searching for a passionate Geospatial Data Engineer to help us curate new training datasets, and develop pipelines to facilitate the ingestion of geospatial datasets into the Radiant MLHub catalog.

What You Will Do:

You will work with Geospatial Software Engineers in our team to process and catalog geospatial machine learning training datasets for use in Radiant MLHub using Python. As part of this process, you will:

• Use Python libraries like rasterio and shapely to read, write, and manipulate spatial data
• Use the SpatioTemporal Asset Catalog (STAC) spec and the associated PySTAC library to catalog geospatial data
• Publish geospatial data and metadata to cloud storage services like Microsoft Azure Blob Storage
• Write, adapt, and maintain Python scripts that combine these tools into reusable data processing pipelines
• Use manual and automated processes to ensure the quality of the processed data and metadata catalogs
• Work with senior developers to integrate scripts into automated workflows

Basic Qualifications:

• Based in either US, Ghana, Ivory Coast, or Senegal, and eligible to work in that country
• Demonstrated experience working with geospatial data and software (GDAL, Shapely, GeoPandas, rasterio)
• Demonstrated experience writing Python scripts to automate tasks
• Working knowledge of SQL
• Working knowledge of version-control platforms (e.g. GitHub, GitLab)
• Attention to detail in ensuring the quality of results and outputs
• Excellent communication skills and ability to collaborate with developers in multiple time zones (primarily in the U.S.) via video conferencing

Preferred Qualifications:

• Experience working with cloud platforms like AWS, Azure, or Google Cloud
• Familiarity with STAC specification

What we offer:

Radiant Earth offers a competitive salary and attractive benefits package with flexible time off. We work with a diverse user community, and you will have the opportunity to work on highly impactful projects. We have a collaborative work environment with a robust support system driven by passionate individuals.

While we sincerely appreciate all applications, only those candidates selected for an interview will be contacted. All applications are considered confidential. Radiant Earth Foundation is an equal opportunity employer.