Software Engineer, Geospatial Systems
$150,000–$220,000 year
On-siteBrooklyn, New York, United States
Job Summary
Software Engineer, Geospatial Systems at Paces—join a team in Brooklyn, NY to research, prototype, and ship core parts of a geospatial engine that supports large-scale spatial search and analysis for renewable energy and infrastructure developers. You’ll work across the full spatial stack (DuckDB, Arrow/GeoArrow, file-based spatial indexing, and an OLTP-backed data lake) and explore geospatial embeddings and foundation models, deciding what to bring into the product. You’ll help set the bar for correctness and performance where wrong or slow answers carry real cost, collaborating with power and permitting experts to accelerate power development.
Required Qualifications
- 4+ years of experience building data intensive software in a similar role
- Strong computer-science fundamentals: data structures, algorithms, graph theory
- Fluency in a systems/backend language
- A track record of building performant, correct backend systems — you can reason about a hot path and read a query plan
- Experience with DuckDB, Apache Arrow, or comparable columnar/analytical data systems
- A research mindset: comfort with open-ended problems, prototyping to learn, and knowing when to harden a prototype into a production system
- Comfort owning ambiguous problems end-to-end and communicating tradeoffs clearly in writing
Desired Qualifications
- 4+ years of experience building data intensive software in a similar role
- Strong computer-science fundamentals: data structures, algorithms, graph theory
- Fluency in a systems/backend language
- Experience with DuckDB, Apache Arrow, or comparable columnar/analytical data systems
- Research mindset: comfort with open-ended problems, prototyping to learn, and knowing when to harden a prototype into production
- Comfort owning ambiguous problems end-to-end and communicating tradeoffs clearly in writing
- Bonus Points: experience with Rust, C, C++, Zig; geospatial / GIS background (PostGIS, GDAL/raster drivers, GeoArrow); ML embeddings or geospatial foundation models; familiarity with zarr / GeoZarr; large-scale spatial pipelines; open source contributor
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