System Soft Technologies
Geospatial Engineer
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Nothing Found.
🌎 - Country
United States
💱 - Currency
$ USD
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💰 - Day rate
Unknown
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🗓️ - Date
May 19, 2026
🕒 - Duration
More than 6 months
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🏝️ - Location
Remote
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📄 - Contract
Unknown
-
🔒 - Security
Unknown
-
📍 - Location detailed
United States
-
🧠 - Skills detailed
#Pandas #Python #Scala #Snowflake #SQL (Structured Query Language) #BigQuery #Strategy #Visualization #Indexing #PostgreSQL
Role description
Job Title: Geospatial Engineer
Location: Richmond, VA (work is remote)
Duration: 6+ months
Primary Responsibility: Design, build, and operate the Geo-spatial solution consisting of large applications with focus on analysis like geocoding, point in polygon, nearest neighbor, grid framework (hexagonal or projected grids) that converts geocoded latitude/longitude data into stable, scalable grid IDs.
Key Responsibilities:
Implement hexagonal hierarchical grids (e.g., H3) or custom projected grids
Convert high-precision geocodes (6-decimal lat/lon) into grid IDs
Manage grid resolution strategy (micro → territory → state)
Building spatial joins for policies, claims, and hazard layers
Generate grid polygons for visualization and QA
Optimize spatial operations for scale (millions of points)
Required Skills:
Open-Source technologies like Geo-server, QGIS
ESRI ArcGIS, ArcGIS Pro, MapInfo
Python (h3, shapely, geopandas, pyproj)
Understanding of hierarchical spatial indexing
Strong geospatial fundamentals (CRS, projections, distortion)
Experience with spatial SQL - PostgreSQL or BigQuery GIS, PostGIS, Snowflake GIS
Job Title: Geospatial Engineer
Location: Richmond, VA (work is remote)
Duration: 6+ months
Primary Responsibility: Design, build, and operate the Geo-spatial solution consisting of large applications with focus on analysis like geocoding, point in polygon, nearest neighbor, grid framework (hexagonal or projected grids) that converts geocoded latitude/longitude data into stable, scalable grid IDs.
Key Responsibilities:
Implement hexagonal hierarchical grids (e.g., H3) or custom projected grids
Convert high-precision geocodes (6-decimal lat/lon) into grid IDs
Manage grid resolution strategy (micro → territory → state)
Building spatial joins for policies, claims, and hazard layers
Generate grid polygons for visualization and QA
Optimize spatial operations for scale (millions of points)
Required Skills:
Open-Source technologies like Geo-server, QGIS
ESRI ArcGIS, ArcGIS Pro, MapInfo
Python (h3, shapely, geopandas, pyproj)
Understanding of hierarchical spatial indexing
Strong geospatial fundamentals (CRS, projections, distortion)
Experience with spatial SQL - PostgreSQL or BigQuery GIS, PostGIS, Snowflake GIS
