Job Description:
• Design and maintain automated ETL pipelines for ingesting real-time hazard and infrastructure data (e.g., power outages, transportation disruptions, weather feeds, supply chain signals).
• Develop Python-based geospatial processing workflows (GeoPandas, Shapely, Rasterio, etc.).
• Build and optimize DuckDB/DuckLake spatial queries.
• Transform large-scale geospatial datasets into analytics-ready formats (Parquet, cloud native formats, GeoJSON, etc.).
• Manage structured and semi-structured data feeds (API integrations, S3 ingestion, streaming updates).
• Support FEMA lifeline monitoring (Energy, Transportation, Food/Water/Shelter, Health & Medical, Communications, etc.).
• Develop spatial risk indices (e.g., outage duration metrics, restoration modeling, supply chain exposure).
• Perform geospatial overlays to assess hazard-economic interdependencies.
• Create repeatable, automated workflows for disaster response reporting.
• Integrate spatial data with economic datasets (IMPLAN, BEA, BLS QCEW, NAICS crosswalks, etc.).
• Support micro- and macro-economic impact modeling workflows.
• Develop location-based analytics for critical industries and supply chain hubs.
• Assist in surge analysis and large-event preparedness (e.g., major storms, national events).
• Support ArcGIS Online / Experience Builder applications.
• Build data services and feature layers optimized for performance.
• Develop scripts to automate map exports and report graphics.
• Support internal analytics platform development (e.g., open-source spatial analytics environments).
• Implement validation checks and logging for data integrity.
• Maintain structured data catalog documentation.
• Troubleshoot spatial data errors (projection issues, geometry corruption, schema inconsistencies).
• Ensure reproducibility and documentation of workflows.
Requirements:
• US Citizenship with ability to obtain a Public Trust.
• Bachelor’s degree in GIS, Geography, Computer Science, Data Science, Engineering, or related field (Master’s preferred).
• 4+ years of professional GIS experience.
• Advanced proficiency in Python (automation, scripting, data processing).
• Strong experience with GeoPandas, Pandas, NumPy, Shapely, Fiona, Rasterio.
• Experience with DuckDB, PostGIS, or spatial SQL.
• Experience with ArcGIS Pro and QGIS.
• Experience handling large geospatial datasets (millions of records).
• Experience working with APIs and cloud storage (AWS S3 preferred).
• Strong understanding of coordinate systems, projections, and spatial indexing.
• Ability to work in high-tempo, disaster-response environments.
• Must be available to support surge operations during emergencies or major events, including the ability to work extended hours outside of the standard schedule as mission needs require.
Benefits:
• Flexible Work Hours
• Remote Work
• Career Growth
• Great People
• Great Environment
• Diversity & Inclusion