About BigGeo
BigGeo is the Spatial Cloud. We help companies manage and access the world’s spatial data. Any size, any slice, any insight. Delivered in seconds.
We’re building something that hasn’t existed before: a new layer of the internet where the “where” and “when” behind every decision is instantly clear, programmable, and actionable. Our platform removes the complexity that has kept spatial data locked in silos for decades, and replaces it with speed, precision, and control.
We’re a Calgary-based company, early and moving fast, with real customers, real infrastructure, and a clear point of view on where the world is going.
Why BigGeo Exits and Why People Build Here
Most companies are spatially blind. They know what their data says, but not where or when things actually happen. That gap costs real money, creates real risk, and limits what AI can actually do in the physical world.BigGeo exists to close that gap.We’re not building another tool. We’re building the rails that connect the planet’s moving data to the systems that run the world. That’s a big problem, and it takes people who care about doing things right, not just fast.
People build here because:
- The problem is real and the category is open. We’re not competing for the middle of an existing market. We’re defining a new one. Your work shapes what the category becomes.
- Your fingerprints are on the architecture. We’re at the stage where the decisions you make today become the foundation tomorrow. What you ship matters.
- We run on clarity, not politics. We move with purpose. No bureaucratic drag, just a team that agrees on the mission and gets to work.
- You’ll grow fast because the problems are hard. Spatial data at scale is a genuinely difficult domain. If you want to be stretched, you’ll be stretched.
- We’re building for longevity. We’re not chasing hype cycles. We’re building infrastructure, the kind that compounds in value over time and earns the trust of the companies that depend on it.
The Role
We're seeking an exceptional Senior Engineer to help architect and accelerate our next phase of growth. In this role, you'll build solutions that change how organizations leverage real-time geospatial data, working at the intersection of computational geometry, high-performance computing, and cutting-edge geospatial technologies.
Key Responsibilities
Design and implement production-grade geospatial libraries with clean APIs and comprehensive documentation
Build high-performance C++ core systems with Python bindings for broad accessibility
Develop and optimize computational geometry algorithms for large-scale spatial analysis
Validate and process complex geometries according to OGC standards
Create deployment strategies and maintain CI/CD pipelines for geospatial services
Collaborate across disciplines to deliver measurable results in high-impact, real-world scenarios
What You Bring
Programming & Software Development
- 7+ years of professional C++ development experience (C++14/17/20)
- Expert-level understanding of modern C++ features, STL, templates, and design patterns
- Strong experience with memory management, performance optimization, and multi-threading
- Proficiency in Python with experience creating FFI bindings (pybind11, ctypes, CFFI)
- Experience building production-grade libraries with clean APIs
- Senior Engineering Practices
- Advanced Git workflows and code review experience
- Proven experience designing deployment strategies for libraries and services
- Strong understanding of semantic versioning, backward compatibility, and API stability
- CI/CD pipeline development and management
- Comprehensive testing practices (unit, integration, performance)
- Experience with build systems (CMake, Bazel) and package management
- Computational Geometry & Mathematics
- Deep understanding of computational geometry algorithms and data structures
- Strong foundation in linear algebra, differential geometry, and numerical methods
- Experience implementing geometric algorithms (convex hulls, spatial decomposition, nearest neighbor search)
- Knowledge of computational complexity and algorithm optimization
- Understanding of floating-point arithmetic and numerical stability
Geospatial & DGGS Expertise
- Solid understanding of coordinate systems, projections, datums, and transformations
- Experience with Discrete Global Grid Systems (H3, S2, or OGC DGGS standards)
- Knowledge of spatial indexing techniques and hierarchical grid structures
- Understanding of geodesic computations and spherical geometry
- Geometry Validation & Processing
- Experience validating geometry according to OGC Simple Features specifications
- Ability to detect and repair invalid geometries (self-intersections, duplicate vertices, incorrect winding order)
- Knowledge of topology rules and spatial relationships
- Experience with geometry simplification, buffering, and overlay operations
- Proficiency with GeoJSON, WKT/WKB formats
- OGC Standards & Data Formats
- Working knowledge of OGC Simple Features Access (SFA) specification
- Understanding of Well-Known Text (WKT) and Well-Known Binary (WKB) formats
- Familiarity with OGC web services (WMS, WFS, WCS, WMTS)
- Experience with modern columnar formats (GeoParquet, GeoArrow)
- Proficiency with Cloud-Optimized GeoTIFF (COG) and raster processing
Nice to Have
- Cloud & Infrastructure
- Kubernetes experience for deploying and scaling geospatial services
- Large-scale cloud compute management (AWS, GCP, Azure)
- Experience with distributed processing frameworks (Spark, Dask, Ray)
- Infrastructure as Code (Terraform, CloudFormation)
- Databases at Scale
- PostGIS competency for spatial database operations
- DuckDB experience for analytical geospatial queries
- Experience with distributed spatial databases and spatial indexing at scale
- Query optimization for large geospatial datasets
- Python Geospatial Processing
- Advanced proficiency in GeoPandas, Shapely, Fiona, Rasterio, GDAL
- Experience creating Python bindings for C++ geospatial libraries
- Knowledge of Python performance optimization (Cython, Numba)
- Advanced Technologies
- Experience with GEOS library, JTS algorithms, or CGAL
- Knowledge of OGC API standards and STAC
- Web development with WebGL, Deck.gl, Mapbox GL JS, or MapLibre
- Point cloud processing (LAS/LAZ, PDAL)
- Computational modeling and simulation frameworks
- Domain Experience
- Background in cartography, GIS, geodesy, or geomatics
- Experience with cadastral or parcel data systems
- Understanding of spatial statistics and geostatistics
- Familiarity with earth observation and satellite imagery processing
Success Metrics
First 30 days:
Onboarded to the Spatial Cloud codebase, geospatial libraries, and current engineering workstreams. Clear understanding of the production systems you will contribute to and the team you will work with most closely.
First 60 days:
Shipped meaningful improvements to at least one production geospatial library or compute system. Contributing to architecture and code reviews with clear written reasoning. Identified at least one area of performance or reliability to improve with a credible plan.
First 90 days and beyond:
Trusted owner of one or more production systems end to end. Your work measurably improves the performance, reliability, or correctness of core Spatial Cloud geospatial infrastructure. Actively shaping how the team builds and ships high-quality spatial systems at scale.