4+ years of data-intensive software development experience
Strong foundation in data structures, algorithms, and graph theory
Proficiency in a systems/backend programming language
Experience building performant, correct backend systems
Familiarity with DuckDB, Apache Arrow, or similar analytical data systems
Research-oriented mindset with a focus on prototyping and production
Ability to handle ambiguous problems and articulate trade-offs effectively
Responsibilities
Research, prototype, and implement key components of the geospatial engine
Transform challenging computational geometry problems into production-ready systems
Work on the entire spatial stack including DuckDB and file-based spatial indexing
Investigate advanced geospatial computation techniques and assess their value
Establish high standards for system correctness and performance
Benefits
401(k) matching
Health, Dental and Vision insurance
Paid company holidays & PTO
Hybrid work arrangement in Williamsburg, Brooklyn (approx. 3 days/week in-office)
Full Job Description
What You'll Achieve
Research, prototype, and ship core parts of the geospatial engine at the heart of Paces - large-scale spatial search and analysis that energy developers depend on.
Take open-ended, hard problems in computational geometry and performance - over tens of millions of parcels and nationwide infrastructure data - from prototype to production.
Work across the full spatial stack: DuckDB, Arrow/GeoArrow, file-based spatial indexing, and a OLTP-backed data lake.
Explore the frontier of geospatial computation - for example geospatial embeddings and foundation models (e.g. Clay) - and decide what's worth bringing into the product.
Set the bar for correctness and performance on a system where wrong or slow answers carry real cost.
Requirements
4+ years of experience building data intensive software in a similar role
Strong computer-science fundamentals: data structures, algorithms, graph theory, and a feel for where time and memory go.
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.
About You
You will thrive in our culture if you:
Correctness and performance matter to you. You measure before you claim, document your tradeoffs, and prefer a loud failure to a plausible wrong answer.
You have real depth in the fundamentals and reach for the right primitive, not the familiar one.
You operate with high agency - you scope ambiguous problems, decide, and own the outcome.
You're pragmatic: you ship the simplest thing that solves a real problem.
Bonus Points
Experience with a systems language - Rust, C, C++, Zig, or similar.
A geospatial / GIS background: PostGIS, GDAL/raster drivers, GeoArrow, projections and coordinate systems, or computational-geometry libraries (GEOS, georust/geo).
ML, embeddings, or geospatial foundation models (e.g. Clay).
Familiarity with zarr / GeoZarr or other large-scale array/raster formats.
Large-scale spatial pipelines, spatial indexing, or distributed/ephemeral compute.
Open source contributor.
Compensation and Benefits
$150K - $220K annual compensation
Competitive equity compensation
401(k) matching
Health, Dental and Vision insurance
Paid company holidays & PTO
Hybrid work in the office in Williamsburg, Brooklyn ~3x per week
