Senior Software Engineer - Geospatial
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AI Summary
You will own and extend the core geospatial engine, focusing on spherical-math correctness and query performance at hyperscale. This involves collaborating with product teams to turn complex customer requirements into robust, high-performance engine capabilities.
Job Title: Senior Software Engineer - Geospatial
Location: 100% Remote (US Based Only)
- We cannot sponsor or transfer any visas, of any kind, at this time*
Hiring Manager: Senior Engineering Manager
Estimated salary range: $165,000 to $190,000
- The salary offered for this position will be based on a candidate’s experience and skill demonstrated during interviews and other evaluations
Job Description:
Ocient has the deepest native geospatial surface in the analytical database market: 120+ native geospatial functions, all built on non-Euclidean spherical math against the WGS84 model of the earth rather than a flattened 2D projection. We store points, linestrings, and polygons natively as columns in SQL-accessible tables, and we run spatial analysis at trillion-row scale on the full-resolution historical data our customers normally have to downsample or throw away.
We are, as far as we know, the only analytical database with native spatiotemporal operators that analyze space and time together directly in SQL rather than forcing two passes over the data. Trajectory and movement analysis that competitors push out to a separate system runs natively here, against data at rest.
We are hiring a Senior Software Engineer to extend that surface. This is a hands-on engineering role on a small team with a lot of surface area, and you will own meaningful pieces of the geospatial engine end to end, from spherical-math correctness to query performance at hyperscale.
What You’ll Work On:
- Core spatial engine. Extend and harden the 120+ geospatial function library across accessors, constructors, measures, predicates, spatial operators, spatial relationships, transformations, and parsers/formatters (WKT, WKB, EWKT, GeoHash).
- Spherical correctness. Work on the numerical correctness of non-Euclidean computation on both the spherical and spheroid WGS84 models: geodesics, great-circle distance, area on a sphere, antimeridian and pole handling, degenerate and near-degenerate geometries, and precision behavior at very small and very large scales.
- Performance and indexing at hyperscale. Make spatial predicates, joins, and range queries fast across trillion-row datasets: spatial indexing, pruning and partitioning strategies, bounding-volume acceleration, vectorized evaluation, and planner integration so spatial filters push down correctly.
- Spatiotemporal analytics. Deepen the space-and-time operator set; trajectory reconstruction, interpolation along linestrings over time, and movement and co-location analysis.
- Convergence with the rest of the engine. Help connect geospatial to Ocient's other analytical surfaces, spatial clustering, accelerated nearest-neighbor search over geographic data, and in-database ML, so spatial and non-spatial analysis compose in a single query and not separate systems
- Customer-driven scope. Geospatial shows up across the industries we target; telco (CDR and cell tower analysis), adtech (geo-targeting), and national security (ISR and movement analysis at scale). You'll work with Product and customer-facing teams to turn those workloads into engine capability.
- Collaboration and craft. Write clear design docs, tests, and documentation so spatial behavior is explicit, benchmarked, and protected against regressions.
Ideal Qualifications:
- 5+ years building production software systems, including solid experience in C++ (or comparable systems-level work with a willingness to work primarily in C++).
- Solid grasp of computational geometry and, critically, spherical/geodetic geometry – you understand why a great-circle distance is not a Pythagorean one and what breaks when you pretend otherwise.
- Exposure to geospatial data, standards, or libraries: WGS84 and geodetic datums, OGC/WKT/WKB, GEOS, S2, H3, PostGIS, or equivalent.
- Comfort with performance engineering such as profiling, algorithmic optimization, and reasoning about work at scale.
- Strong instincts around numerical correctness and edge cases, and the discipline to encode them in tests and documentation.
- Ability to work across teams and codebases and turn ambiguous requirements into concrete solutions.
An Exceptional Candidate Will Have:
- Experience implementing spatial indexing or spatial query optimization inside a database or query engine.
- Background in trajectory analysis, spatiotemporal data management, or moving-object databases.
- Experience with large-scale data systems, analytical databases, query planners, or distributed execution.
- Familiarity with in-database ML, or with optimization and spectral methods applied to geographic problems
- Domain experience in one of our target verticals such as telco, network analysis, adtech, automotive/mobility, aviation, logistics, or government/geospatial intelligence.
What Success Looks Like:
- Ocient’s spatial function library stays the most complete and most accurate in the market, and our lead widens rather than erodes.
- Spatial queries that customers previously had to downsample, pre-aggregate, or move off-platform now run interactively at full resolution.
- Spherical-math correctness is provable – validated against reference implementations, with edge cases documented rather than discovered by customers.
- Spatiotemporal analysis becomes a capability we lead with in deals, not a feature buried in the docs.
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