Geospatial Data Engineer
Responsibilities
- Development experience in Python – either a Computer Science or scientific computing background or demonstrated professional experience in team-oriented software development using GitHub or other source control systems
- Experience working in with cloud tools and infrastructure (with preference for experience with Google Cloud)
- Experience with common geospatial and scientific Python libraries: GDAL, Rasterio, GeoPandas, NumPy, SciPy, and others
- Comfort with common geospatial data types: both raster (GeoTIFF/COG/ZARR/NetCDF/GRIB) and vector (SHP/GeoJSON/others)
- Experience or background in any of the following is a big plus: BigQuery, Dask, ZARR, STAC, data visualization, remote sensing, meteorological data production
- Deep educational experience in a specific geoscience domain is not necessary
- Very strong attention to detail
- A thought process towards generalization and reducing future data or technology debt
- Comfort with data from a wide variety of geoscience domains
Requirements
- Excellent communication skills (spoken and written)
- Bachelor’s degree in mathematics, statistics, computer science or related field
- Two to three years’ experience working with large data analysis
- Any experience in remote sensing, geospatial data science, geographic information systems or equivalent field would be preferred but not mandatory
- Proactive, self-starter, able to work independently and drive results
- Critical thinking and strong organizational skills