Senior GIS / Geospatial Engineer — Part-Time Advisor for U.S. Media Intelligence Platform

Senior GIS / Geospatial Engineer — Part-Time Architect for AI-Enabled Media Intelligence Platform About the project We are building a new geospatial layer for Maven, a media intelligence platform that maintains structured data on U.S. media properties, ownership, companies, and related information. We want to connect our existing media and ownership graph to a comprehensive geographic foundation covering the United States. The product will ultimately allow users to: Search any ZIP, city, county, metro, or other geography Draw custom areas on a U.S. map Return the ZIPs, counties, population, households, and demographics within that area Map media properties and their owners Determine which media serve or cover a geography Classify areas as urban core, suburban, exurban, rural, etc. Overlay customer or campaign data Build and export custom market/media universes Support natural-language queries such as: “What independent newspapers cover urban San Francisco?” We already have two strong full-stack engineers working with React/TypeScript, Python/FastAPI, PostgreSQL, Elasticsearch, and graph databases. We are looking for a senior GIS/geospatial specialist to work alongside our engineering team and help us design the geographic foundation correctly from the beginning. What we need help with The initial work will focus on architecture, data ingestion, and GIS best practices. Key areas include: Designing a scalable PostgreSQL/PostGIS geographic data model Advising on geometry types, projections, coordinate systems, simplification, and spatial indexing Designing relationships between ZIP/ZCTA, census tract, block group, city/place, county, CBSA/metro, urban area, and custom geographies Ingesting and normalizing U.S. Census TIGER/Line and Gazetteer datasets Integrating ACS population and demographic data Working with USDA RUCA and Census commuting data for urban/suburban/exurban/rural classifications Advising on FCC station and broadcast-contour data Designing polygon intersection and population aggregation workflows Helping determine when to use PostGIS queries vs. H3 vs. vector tiles Advising on MapLibre, deck.gl, PMTiles, and scalable web-map architecture Reviewing spatial ETL pipelines using Python, GeoPandas, Shapely, GDAL, and/or DuckDB Spatial Performance testing and validation of national-scale spatial queries Establishing geographic data QA, provenance, and versioning practices We do not expect this person to build the entire application. Our existing engineers will handle most backend and frontend development. The ideal person will help us establish the architecture, review implementations, solve difficult geospatial problems, and transfer GIS knowledge to our engineering team. Ideal background Strong experience with: PostgreSQL / PostGIS Python geospatial tooling GeoPandas Shapely GDAL GeoJSON Spatial indexing and spatial SQL U.S. Census geography and TIGER/Line Large-scale polygon intersection and aggregation Experience with some of the following is especially valuable: MapLibre GL deck.gl H3 PMTiles Planetiler or Tippecanoe DuckDB Spatial Census ACS Census LODES USDA RUCA FCC geographic / broadcast data Geocoding systems Nationwide web GIS applications Experience building production web GIS products is much more important to us than experience creating static maps in ArcGIS. AI-assisted development We work in an AI-enabled engineering environment and are looking for someone comfortable using modern AI development tools to accelerate software development, research, debugging, testing, and documentation. Experience with tools such as ChatGPT, Claude, Cursor, GitHub Copilot, Codex, or similar AI coding agents is a plus. We are particularly interested in candidates who know how to use AI effectively for: Writing and reviewing Python, SQL, and PostGIS code Building and debugging spatial ETL pipelines Generating tests and validation routines Exploring unfamiliar datasets and APIs Reviewing architecture and identifying edge cases Producing technical and data-source documentation Accelerating repetitive GIS and data-engineering tasks AI experience is not a substitute for strong GIS fundamentals. We are looking for someone who can combine deep geospatial expertise with modern AI-assisted engineering workflows. Initial engagement We expect this to begin as a part-time consulting engagement. Likely commitment: 5–10 hours per week initially, with the ability to increase temporarily during major architecture or data-ingestion milestones. The initial engagement will likely run approximately 2–4 months, with the potential for ongoing advisory work. First milestones We would like the consultant to help our engineering team accomplish: Review and finalize the Maven geographic architecture Establish the PostGIS schema and spatial standards Load U.S. Census geography into the platform Establish demographic joins and aggregation methodology Design our urban/suburban/exurban/rural methodology Validate custom-polygon analysis Review the architecture for mapping tens of thousands of media properties nationally Establish performance and scaling recommendations When applying Please include: Examples of production GIS or web-mapping systems you have built Your experience with PostGIS Your experience with U.S. Census/TIGER data Any experience with MapLibre, deck.gl, H3, PMTiles, or related technologies How you would approach building a nationwide geographic intelligence layer using PostGIS A brief description of how you currently use AI coding or research tools in your engineering workflow, if applicable We are particularly interested in someone who can act as a technical GIS architect and mentor to an experienced software engineering team, rather than someone who primarily performs manual GIS analysis.