Senior Geospatial Software Engineer

7 hours ago

Dehra Dūn, Uttarakhand, India beBeeGeospatial Full time ₹ 25,00,000 - ₹ 40,00,000

We are seeking an experienced Full Stack Developer to lead our geospatial web application projects. The ideal candidate will possess expertise in Python and GIS technologies, as well as a strong understanding of front-end development principles.

This role involves designing, developing, and maintaining scalable geospatial web applications that deliver seamless functionality and optimal performance. The successful candidate will work collaboratively with cross-functional teams to integrate spatial data with front-end and back-end systems.

Key Responsibilities:

  • Design and Development: Develop geospatial web applications using Python and frameworks like Django or Flask.
  • GIS Mapping: Implement interactive, dynamic GIS maps using libraries such as GeoPandas, Shapely, and Folium.
  • Data Integration: Integrate geospatial data with databases and RESTful APIs.
  • Automation: Automate geospatial data processing workflows using Python libraries like ArcPy, Fiona, or PyQGIS.
  • Front-End Development: Build responsive front-end interfaces using HTML, CSS, JavaScript, and frameworks like React, Angular, or Vue.js.
  • Collaboration: Collaborate with data scientists and GIS analysts to productionize geospatial models and visualizations.
  • Optimization: Optimize applications for performance, scalability, and reliability.
  • Troubleshooting: Troubleshoot and debug issues across the full stack.

Required Skills and Qualifications:

  • Bachelor's Degree: Bachelor's degree in Computer Science, Geographic Information Systems, or a related field.
  • Full Stack Experience: Proven experience as a Full Stack Developer with strong proficiency in Python.
  • GIS Expertise: Expertise in GIS technologies and Python libraries such as GeoPandas, Shapely, Fiona, ArcPy, or PyQGIS.
  • Front-End Technologies: Experience with front-end technologies including HTML, CSS, JavaScript, and frameworks like React, Angular, or Vue.js.
  • Database Technologies: Familiarity with database technologies, particularly PostgreSQL with PostGIS for geospatial data.
  • RESTful APIs: Knowledge of RESTful APIs, web services, and data integration from various sources.
  • Version Control: Proficiency with version control systems, particularly Git.

Preferred Skills:

  • Cloud Platforms: Experience with cloud platforms like Google Cloud Platform (GCP), AWS, or Azure for deploying GIS applications.
  • ESRI ArcGIS Suite: Familiarity with ESRI ArcGIS Suite (ArcPro, ArcMap) or QGIS for geospatial analysis.
  • MLOps Practices: Knowledge of MLOps practices for integrating machine learning models with GIS applications.
  • Geospatial Data Formats: Understanding of geospatial data formats and spatial analysis techniques.

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