Full Stack Developer

Job Description for Full Stack Developer

We are seeking a highly skilled Full Stack Developer to design, build, and maintain interactive DSS, platforms and dashboards that integrates remote sensing data, AI-driven analytics, and real-time environmental monitoring.

Key Responsibilities:

• Develop and maintain scalable web-based applications and dashboards to visualize urban heating patterns, aquaculture mapping and real-time analytics.
• Design robust back-end systems to manage large geospatial datasets, real-time sensor feeds, and AI model outputs.
• Work with data scientists and image analysts to integrate remote sensing products, AI results, and spatial layers into the application.
• Implement APIs for data ingestion, processing, and delivery from various sources (e.g., satellites, IoT sensors, weather systems).
• Ensure responsive front-end design with intuitive visualizations of heat maps, time-series graphs, and spatial analytics.
• Optimize application performance, security, and scalability in cloud or hybrid environments.
• Collaborate with GIS team and contribute to technical documentation, version control, and continuous integration pipelines.

Requirements

• Master’s degree in Computer Science, Software Engineering, Geo informatics, Geospatial Data Science or related field.
• 3-5 years of experience in full-stack web development with proven experience in data-heavy applications.
• Strong proficiency in Python for back-end development and data processing (Flask, Django, or FastAPI); experience building services that integrate AI/ML outputs.
• Proven experience with Node.js, Express.js and RESTful API development for building backend services.
• Hands-on experience with front-end technologies (React.js) data visualization libraries and mapping frameworks such as D3.js, Leaflet, Mapbox GL, or Deck.gl.
• Experience working with spatial databases (PostGIS, MongoDB, etc.) and cloud services (AWS, Azure, GCP).
• Understanding of remote sensing data structures, raster/ vector handling, and integration of geospatial analytics.
• Familiarity with AI/ML model deployment and real-time data integration (e.g., MQTT, WebSockets).
• Familiarity with ETL based Workflows (Preferable)