Job Title: Geospatial Software Engineer

Company Name: Knowmadics, Inc

Job Url: https://www.simplyhired.com/job/c-pQWjhwW2cSApOSLmYihC6zhvpZFyZYkjjRgqUcItAW2KOuPxWmeg

Job Description: Software Engineer, Geospatial
Knowmadics, Inc
Wichita, KS

Job Details
Full-time
20 hours ago
Qualifications
Spatial analysis
Bayesian inference
Data transformation pipeline development
Machine learning/AI-based analysis
Continuous Delivery (CD) implementation
PostGIS
Infrastructure as Code (IaC)
Spark
Git
Research
Mid-level
Scalable systems
JavaScript frameworks
SQL
AWS
Spark implementation
Docker
Cloud Native Design
Scalability
Developing and maintaining backend systems
Web applications
Kafka
Data visualization
Clustering
AI
Cross-functional collaboration
Data visualization projects
Python
Database software proficiency
Full 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