Sobre

We have a fully built, production-ready React frontend for a B2B Real Estate Due Diligence platform ("Rio Grande Due Diligence"). The UI and frontend logic are complete. We need a Senior Backend Developer to build the geospatial engine (Python/PostGIS) that powers it. View the Live Frontend Here: https://nm-landguard.lovable.app (Review this link before applying to understand the scope.) THE MISSION: You will build the "Brain" that connects to this "Body." You will write the Python scripts that query government APIs, analyze the data, and generate professional PDF and KMZ reports. CORE DELIVERABLES: 1. The "10-Pillar" Data Engine (Python): Write robust scripts to query 10 specific APIs/Data Layers based on user coordinates or polygon inputs: Historic: NMCRIS / HPD Spatial Buffers. Water: NM Office of State Engineer (OSE) Basins & Wells. Bio: USFWS IPaC (Critical Habitat). Flood: FEMA NFHL API. Energy: NM OCD (Oil/Gas Pipelines). Geotech: USDA SSURGO (Soil) & USGS 3DEP (Slope/Elevation). Infrastructure: Google Places (Fire/Hospital) & Google Solar API. Wildfire: USFS Risk Data. 2. The "Risk Radar" Algorithm: Implement a scoring logic that normalizes these 10 disparate data points into a 0-100 "Risk Score" for the frontend Radar Chart visualization. 3. The "Pro Export" Suite: Dynamic PDF: Generate a 6-page professional PDF report with dynamic maps, data tables, and citations. KMZ Generation: Generate a Google Earth (.kmz) file overlaying the parcel boundary and identified risk buffers. 4. Integration: Connect the existing "Generate Site Assessment" button to a Stripe Checkout webhook. Ensure the "System Status" ticker on the frontend reflects simple API health checks. REQUIREMENTS: Expertise in PostGIS, GDAL, and Python Geospatial libraries (GeoPandas, Shapely). Experience generating KMZ/KML files programmatically. Ability to work with existing React/Supabase code to connect the backend.