Capability
Geospatial Data & Analysis
Geographic data built from disparate sources and made usable by people who are not GIS specialists: spatial ETL, interpolation across mismatched geographies, Earth observation data, and the analytics and AI on top.
Problems I Solve
Where this capability fits
Sources arrive at different geographies and granularities, with no shared identifier to join on.
Spatial data is scattered across incompatible formats, projections, and coordinate systems.
Satellite and Earth observation catalogs are powerful but hard to reach from the desktop tools analysts already use.
Maps exist, but they are not connected to the pipelines, warehouses, and models the rest of the business runs on.
Scope
Capabilities
Spatial ETL and automation for building geographic data assets
Projections, coordinate reference systems, and spatial data validation
Population-weighted areal interpolation across mismatched geographies (DMA, CBSA, county, tract)
PostGIS spatial database design and spatial SQL
Google Earth Engine catalog access: Sentinel-5P and the full data catalog
QGIS plugin development (PyQGIS, PyQt6)
Spatial joins, enrichment, and anomaly detection
Boundary changes over time, such as redrawn congressional districts
Example Systems
Systems I design and build
Geospatial data engines that fuse census, financial, and search data for research
Earth observation data access inside desktop GIS
Civic and electoral maps that track boundary changes
Spatial analysis delivered as dashboards for non-GIS users
Technical Stack
Tools and platforms
Need this capability on your product?
Start with a technical scoping call focused on data sources, users, and success criteria.