Python GIS Full Stack Developer

Job Summary

Python GIS Full Stack Developer

Experience

1.5 - 2 years

Salary

25K - 40K

Responsibilities

• Develop and maintain GIS-based web applications using Python and frameworks like Django or Flask.
• Design and implement interactive, dynamic GIS maps using libraries such as GeoPandas, Shapely, and Folium.
• Integrate geospatial data with databases (e.g., PostgreSQL/PostGIS, MySQL, or MongoDB) and RESTful APIs.
• Automate geospatial data processing workflows using Python libraries like ArcPy, Fiona, or PyQGIS.
• Build responsive front-end interfaces using HTML, CSS, JavaScript, and frameworks like React, Angular, or Vue.js.
• Collaborate with data scientists and GIS analysts to productionize geospatial models and visualizations.
• Optimize applications for performance, scalability, and reliability.
• Troubleshoot and debug issues across the full stack, from front-end interfaces to back-end data pipelines.
• Manage deployment and continuous integration processes using tools like Docker, Kubernetes, or CI/CD pipelines.
• Stay updated with the latest GIS and web development technologies and best practices.

Qualifications

• Bachelor’s degree in Computer Science, Geographic Information Systems, or a related field (or equivalent experience).
• Proven experience as a Full Stack Developer with strong proficiency in Python.
• Expertise in GIS technologies and Python libraries such as GeoPandas, Shapely, Fiona, ArcPy, or PyQGIS.
• Experience with front-end technologies including HTML, CSS, JavaScript, and frameworks like React, Angular, or Vue.js.
• Familiarity with database technologies, particularly PostgreSQL with PostGIS for geospatial data.
• Knowledge of RESTful APIs, web services, and data integration from various sources.
• Proficiency with version control systems, particularly Git.
• Strong problem-solving skills and attention to detail.
• Excellent communication and teamwork abilities.

Preferred Skills

• Experience with cloud platforms like Google Cloud Platform (GCP), AWS, or Azure for deploying GIS applications.
• Familiarity with ESRI ArcGIS Suite (ArcPro, ArcMap) or QGIS for geospatial analysis.
• Knowledge of MLOps practices for integrating machine learning models with GIS applications.
• Experience with containerization (e.g., Docker) and orchestration (e.g., Kubernetes).
• Understanding of geospatial data formats (e.g., GeoJSON, Shapefiles, KML) and spatial analysis techniques.

Benefits

• Competitive salary and comprehensive health benefits.
• Opportunities for professional growth and development.
• Collaborative and innovative work environment.
• Flexible remote or hybrid work options (location-dependent).

How to Apply

business@drdesignindia.com

Join us in creating cutting-edge geospatial solutions that drive impactful decision-making!