Role overview
- Location: This position is a fully remote position within an engaged, virtual division at NV5.
- Travel <10% of the time
- Proof of U.S. Citizenship is required.
Responsibilities
- Translate business requirements into technical specifications, data models, data streams, and databases
- Develop production ready geospatial workflows and data pipelines using open-source python libraries
- Work with online transaction processing (OLTP) and online analytics processing (OLAP) stacks (PostgreSQL, DuckDB, PyArrow, Parquet / GeoParquet)
- Develop spatial computation with H3, Shapely, GDAL/OGR and other lightweight geospatial utilities
- Write testable, benchmarked code using pytest and async test patterns
- Build with python package managers like uv and poetry utilizing pyproject.toml for project management
- Collaborate in open-source–style repositories with linting, formatting, typing, and CI expectations
- Build CI/CD pipelines with integrated unit tests
- Convert or embed ML/AI workflows into production-grade, enterprise systems
- Utilize Research, Plan, Implement strategies for AI-driven development practices
- Design, develop, and maintain infrastructure for geospatial analysis and ML/AI applications on large data
Basic qualifications
- Bachelor’s degree from an accredited university in Computer Science, Information Technology, or a related field
- 5 years of experience in data science, geospatial, IT, ML/AI, or related field
- Must have had a Department of Defense Common Access Card in the past two years
- Data/database architecture design within cloud computing infrastructure
- Systems analysis
- Experience working with Geospatial data
- Strong Python engineering experience in production systems
- Proven ability to design efficient spatial data pipelines
- Experience working with spatial data analysis at scale
- Comfort developing CI/CD pipelines and unit tests
- Comfort working in backend systems that integrate with LLMs and AI
- Comfort working as part of a software development team
- Strong focus on correctness, reproducibility, and explainability
- Strong written and verbal communication skills
- Web map application development
- Performing data analysis
- Experience with Research, Plan, Implement strategies for AI-driven development practices
- RAG and embeddings AI application development experience
- Background in geospatial analytics outside traditional GIS stacks
- Experience with data lakehouse platforms such as Databricks
- Familiarity with a variety of geospatial data formats
- Understanding of geospatial metadata requirements
- Security+ Certification
- Python
- Apache Spark
- PostGIS
- PostgreSQL
- MySQL
- Databricks Platform
- FOSS GIS Software (GDAL/OGR, PROJ, Leaflet, etc.)
- FOSS GIS Platforms (GeoServer, QGIS, GRASS GIS)
- Esri GIS Platforms (Desktop/Enterprise/Online)
Tags & focus areas
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