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Posted 1mo ago

Software Engineer, Geospatial

@ Knowmadics
Wichita, Kansas, United States
OnsiteFull Time
Responsibilities:Design pipelines, Develop analytics, Operate APIs
Requirements Summary:3+ years geospatial software engineering; strong Python geospatial stack; ETL pipelines; full-stack Python + React; AWS; Docker/Kubernetes; eligible for U.S. security clearance.
Technical Tools Mentioned:Python, GeoPandas, Shapely, PyProj, PostgreSQL, PostGIS, TimescaleDB, FastAPI, Pydantic, React, Cesium, Mapbox, MapLibre, Docker, Kubernetes, AWS
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Job Description

Job Purpose/Summary 

 

The Geospatial Software Engineer designs, builds, and operates scalable geospatial systems that transform complex spatial-temporal and sensor-derived data into analytics, visualizations, and web-based applications. This role spans the full data path from curated datasets and geospatial processing pipelines through to low-latency APIs and analyst-facing, map-based tools. 

  

Working across backend infrastructure and front-end visualization, the engineer transforms spatial-temporal data and develops robust analytics. They ensure that data pipelines, databases, and web applications are performant, reliable, and designed for real-world operational use. 

  

In close collaboration with data scientists, geophysicists, and cross-functional engineering teams, this role translates advanced research and sensor analytics into scalable systems. As part of a fast-moving, government-funded technology business, the Geospatial Software Engineer operates with high ownership in an applied research environment focused on delivering impactful, mission-driven solutions. 

 

Duties and Responsibilities 

  • Design and build scalable geospatial data pipelines from curated data 
  • Develop and operationalize spatial-temporal analytics, including movement characterization, clustering, and advanced spatial transformations. 
  • Translate complex geospatial workflows into reliable, low-latency APIs that power web-based analytical tools. 
  • Build and maintain interactive, map-based applications for analysts exploring sensor-derived, spatial-temporal data. 
  • Deploy and operate services in a cloud-native environment using containerized infrastructure. 
  • Collaborate with data scientists and domain experts to operationalize advanced analytics into robust systems. 
  • Take ownership of features from backend ingestion through to front-end visualization in an applied research environment. 

 

Qualifications 

 

Minimum: 

  • 3+ years of hands-on geospatial software engineering experience. 
  • Strong Python geospatial experience, including libraries such as GeoPandas, Shapely, PyProj, and similar tooling. 
  • Solid understanding of spatial modelling, projections, zonal statistics, and spatial transformations. 
  • Experience working with spatial-temporal datasets. 
  • Experience building ETL/data pipelines loadingdata into operational databases such as PostgreSQL with PostGIS/TimescaleDB. 
  • Experience developing full-stack applications using Python-based backends, FastAPI/Pydantic preferred, and modern JavaScript front-end frameworks with React. 
  • Experience building geospatial visualizations using libraries such as Cesium, Mapbox/MapLibre, or Lonboard. 
  • Experience working in AWS or similar cloud environments. 
  • Experience deploying containerized applications using Docker and familiarity with Kubernetes. 
  • Eligible to obtain a U.S. Security Clearance – U.S. Citizenship required 

Preferred: 

  • Direct experience processing geophysical, sensor, or seismographic data. 
  • Experience developing CI/CD pipelines for data services using Git-based workflows and infrastructure-as-code principles. 
  • Experience with event-driven or streaming data systems e.g. Kafka, Spark, Flink, or Sedona. 
  • Experience with lakehouse-style analytical tables e.g. Iceberg or Delta  
  • Experience with SQL query engines e.g. Trino, DuckDB, or Athena 
  • Strong production experience with PostgreSQL with PostGIS and TimescaleDB extensions at scale. 
  • Experience working with cloud-native geospatial architectures and cloud-optimized formats. 
  • Experience scaling geospatial workloads in Kubernetes-based environments. 
  • Experience applying ML/AI techniques, e.g. Bayesian methods and neural networks, to spatial-temporal datasets. 
  • Background in defense, cybersecurity, space, or other mission-driven sensor analytics environments. 

Working conditions 

 

  • Employees may be called upon to participate in in-person meetings, trainings, or company functions at Knowmadics offices or other designated locations. Travel in support of business operations may also be required, and employees are expected to comply with these obligations as part of their position. 

 

 

Physical requirements 

 

May include sitting or standing for extended periods, working with computers and technical equipment, and occasionally lifting or moving materials or tools. 

 

Direct reports 

 

None