Geospatial Data Engineer
Shearwater Aerospace
- Quebec City, QC
- Permanent
- Full-time
- Design geospatial processing pipelines that balance performance, accuracy, and extensibility
- Build GIS analysis algorithms for weather-aware route optimization
- Integrate multi-source datasets (elevation, obstacles, airspace, meteorological models)
- Create APIs that enable real-time flight decision-making
- Establish patterns and tooling that evolve as our platform matures
You can explain why you chose PostGIS over alternative spatial databases, or when to pre-process vs. compute on-demand. You know the geospatial database landscape and select tools based on requirements, not trends. You're comfortable defending your decisions and pivoting when new constraints emerge.You stay current and execute rigorously.
You follow modern geospatial best practices and understand OGC standards. You keep up with evolving tools and approaches instead of relying on outdated tooling.You've shipped production GIS systems.
You've wrestled with coordinate transformations, spatial indexing, and raster processing. You know the common GIS tools and libraries—GDAL/OGR, various spatial databases, processing frameworks—and understand when each fits. Bonus: you've worked with meteorological data (NetCDF, GRIB) or atmospheric models.You're comfortable with ambiguity.
Requirements evolve. Priorities shift. You ask clarifying questions, propose solutions, and deliver incrementally rather than waiting for perfect specs.You communicate clearly.
You can explain technical trade-offs to non-engineers and translate vague product needs into concrete implementation plans. Ego doesn't enter the room when someone questions your approach.Technical Foundation We're Looking ForCore GIS competency:
- 4+ years building geospatial software (or 3 years if you've shipped impressive systems)
- Strong knowledge of common GIS tools and libraries (QGIS, GDAL/OGR)
- Experience with geospatial algorithms (visibility analysis, spatial operations, terrain analysis)
- Deep understanding of coordinate systems, projections, and spatial data structures
- Strong Python with scientific computing stack (NumPy, Pandas, SciPy)
- Geospatial libraries: GeoPandas, Rasterio, Xarray, Dask
- Experience with spatial databases (PostGIS, Apache Sedona, etc)
- Comfortable with cloud infrastructure (GCP preferred), Docker, Git
- Ability to set up automated data ingestion workflows
- C/C++ for performance-critical processing
- Meteorology, atmospheric science, or aviation background
- Degree in GIS, Computer Science, Engineering, or related field. Master's is a plus, but we'll prioritize what you've built over credentials.