About the role

Geospatial Data Engineer building data processing systems for autonomous flight decisions alongside the CTO. Architecting systems evolution from initial implementation to production-grade infrastructure.

Responsibilities

You'll be our first geospatial hire, building the data processing systems that enable autonomous flight decisions.
Working with our CTO, you'll architect how our systems evolve from initial implementation to production-grade infrastructure that handles real-world operational demands.
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.

Core 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
Python ecosystem: Strong Python with scientific computing stack (NumPy, Pandas, SciPy)
Geospatial libraries: GeoPandas, Rasterio, Xarray, Dask
Data infrastructure: Experience with spatial databases (PostGIS, Apache Sedona, etc)
Comfortable with cloud infrastructure (GCP preferred), Docker, Git
Ability to set up automated data ingestion workflows
Nice to have: 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.

Equity ownership – You're building foundational systems. You should own a meaningful piece of what we're creating.
Architectural influence – This isn't "implement the spec." You'll shape technical decisions alongside the CTO as we define what autonomous flight infrastructure looks like.
Hybrid flexibility – Work where you're most productive. We're in Montreal but value focus time and thoughtful collaboration over face-time.
Growth with the platform – You'll evolve systems as we mature from initial architecture to production-hardened infrastructure. The foundations you establish will scale with increasing mission complexity, data volumes, and operational demands—and you'll architect that evolution.
Direct impact – Your code runs onboard aircraft making critical flight decisions. You'll see your work enable missions that weren't possible before, extending operational capabilities in real-world conditions.