255-18 Python Dev (API/BACKEND)

Location: Hybrid, Lansing

Job Type: 1099

We are seeking a skilled and adaptable Python Software Engineer to join our team. This role is ideal for someone who thrives in dynamic environments, takes full ownership of their code from development to deployment, and is passionate about building robust, scalable, and maintainable systems.

• End-to-End Script Ownership: Develop, test, and deploy Python scripts from local environments to production web servers, ensuring reliability and performance.
• API Development & Integration: Design and implement secure, well-structured APIs for internal and external use. Integrate with third-party APIs and services as needed.
• Adaptable Data Handling: Modify and enhance existing codebases to accommodate changes in data structures, sources, or API specifications, while maintaining data integrity and robust error handling.
• System-Level Awareness: Understand and manage the broader system context in which your code runs, including environment setup, dependency management, and inter-service communication.
• Request-Driven Development: Build server-side logic to handle incoming requests (e.g., RESTful endpoints, webhooks), with proper validation, logging, and response mechanisms.
• Deployment & Operational Competence: Deploy Python applications using tools like Flask or FastAPI with Gunicorn and Nginx. Manage configurations and troubleshoot runtime issues in production environments.
• Clean Code & Maintenance: Write modular, testable, and maintainable code with clear documentation and logging to support long-term maintenance and team collaboration.
• Problem Solving Under Constraints: Quickly debug and resolve integration issues, especially when working with evolving third-party APIs or changing data requirements.

• Strong proficiency in Python 3
• Experience with API development and integration
• Familiarity with web frameworks such as Flask or FastAPI
• Solid understanding of deployment pipelines and web server configurations (e.g., Nginx, Gunicorn)
• Ability to handle data transformations and work with various data formats and sources
• Experience with version control systems (e.g., Git)
• Strong debugging and problem-solving skills

Libraries & Tools:

• matplotlib
• pyyaml
• geopandas
• numpy
• scipy
• pandas
• gdal
• fiona
• rasterio>=1.0
• rasterstats
• shapely
• rtree
• pyproj>=2.0
• pyshp
• xlrd
• openpyxl
• requests
• pytest

Deployment & Hosting:

Python runtime with web server and API exposure (e.g., Nginx + Gunicorn/Flask); final tooling to be determined.

• Experience with geospatial data processing
• Familiarity with CI/CD pipelines
• Exposure to cloud platforms (AWS, GCP, Azure)