Full Stack Geospatial Developer

1 week ago

Mysore, Karnataka, India beBeeGeographic Full time ₹ 25,00,000 - ₹ 40,00,000

We are seeking a skilled professional to join our team as a GIS Full Stack Developer.

This is a full-time opportunity that requires the ability to design, develop and maintain geospatial web applications using Python and various GIS technologies.

Key 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 and RESTful APIs.
  • Automate geospatial data processing workflows using Python libraries like ArcPy, Fiona and 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 and CI/CD pipelines.

Requirements:

  • 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.

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