GIS Python Developer

Overview

About Niyam IT (Niyam) Niyam IT was founded in 2007 by a group of consultants who shared a unique vision: a technology company steeped in orderly process yet driven by passion and innovation. Today, Niyam is at the forefront of the industry, leading the way in crafting mission-critical technologies for Emergency Preparedness & Response, Natural Resource Management, Law Enforcement & Justice, Health IT, and Global Citizen Services.

Join us in creating a workplace where innovation, diversity, and well-being thrive. Your journey at Niyam IT awaits. Apply today!

Niyam IT is seeking a GIS Python Developer to join our team in support of a high-impact federal program. The GIS Python Developer plays a vital role in supporting national preparedness, response, and recovery efforts by building dependable geospatial data solutions that help decision makers understand evolving hazards and infrastructure impacts. This position develops and maintains automated data pipelines that ingest real time information such as power outages, transportation disruptions, weather feeds, and supply chain signals, transforming large and complex datasets into clear, actionable insights.

Using Python and modern spatial tools, the developer creates efficient geospatial workflows, performs detailed spatial analysis, and develops risk indicators that highlight impacts to critical lifelines including energy, transportation, communications, food, water, shelter, and health systems. Working closely with analysts, emergency managers, and technical teams, the role integrates spatial and economic data to support impact modeling, disaster reporting, and planning for major events, while also supporting ArcGIS Online applications and dashboards, ensuring data quality and documentation, and resolving spatial data issues to maintain accuracy and reliability in fast paced, mission focused environments.

Position currently allows remote work.

• 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 (Geo Pandas, Shapely, Rasterio, etc.).
• Build and optimize DuckDB/Duck Lake 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.

• 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 Geo Pandas, Pandas, Num Py, Shapely, Fiona, Rasterio.
• Experience with DuckDB, PostGIS, or…