Senior Geospatial Application Developer

3 days ago

Belgaum, Karnataka, India beBeeGeographic Full time ₹ 2,50,000 - ₹ 4,00,000
GIS Web Developer

Job Description:

We are seeking a skilled and innovative Full Stack GIS Developer to design, develop, and maintain geospatial web applications. This role requires expertise in Python and GIS technologies to deliver scalable, user-friendly solutions.

The ideal candidate will have experience with front-end development using HTML, CSS, JavaScript, and frameworks like React, Angular, or Vue.js. They should also be familiar with database technologies, particularly PostgreSQL with PostGIS for geospatial data.

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 Arpy, Fiona, or PyQGIS.

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, Arpy, 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).

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