Full-Stack Geospatial Web Developer

4 days ago

Kanpur, Uttar Pradesh, India beBeeGeographic Full time ₹ 2,50,000 - ₹ 4,00,000
Job Title: Full Stack GIS Developer

Summary:

Our organization is seeking a skilled Full Stack GIS Developer to design, develop, and maintain geospatial web applications.

Responsibilities include:

  • Designing and implementing interactive, dynamic maps using libraries such as GeoPandas, Shapely, and Folium.
  • Developing and maintaining GIS-based web applications using Python and frameworks like Django or Flask.
  • Integrating geospatial data with databases (e.g., PostgreSQL/PostGIS, MySQL, or MongoDB).
  • Automating geospatial data processing workflows using Python libraries like ArcPy, Fiona, or PyQGIS.
  • Building responsive front-end interfaces using HTML, CSS, JavaScript, and frameworks like React, Angular, or Vue.js.
  • Collaborating with data scientists and GIS analysts to productionize geospatial models and visualizations.
  • Optimizing applications for performance, scalability, and reliability.
  • Troubleshooting and debugging issues across the full stack, from front-end interfaces to back-end data pipelines.
  • Managing deployment and continuous integration processes using tools like Docker, Kubernetes, or CI/CD pipelines.

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 Qualifications:

  • 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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