Full Stack Developer

• Develop and maintain scalable web applications, platforms, dashboards, and decision-support systems for data-driven applications.
  
• Design and develop robust backend systems for managing large geospatial datasets, analytical outputs, and real-time data streams.
  
• Work with data scientists, image analysts, and GIS teams to integrate remote sensing products, AI/ML outputs, and spatial datasets into web applications.
  
• Design and implement REST APIs for data ingestion, processing, integration, and data delivery from multiple sources.
  
• Develop responsive and intuitive front-end interfaces for visualizing maps, spatial layers, time-series data, analytical outputs, and interactive visualizations.
  
• Implement efficient handling and visualization of raster, vector, and other geospatial data formats.
  
• Optimize application performance, reliability, security, and scalability across cloud or hybrid environments.
  
• Design and support ETL and data-processing workflows for integrating heterogeneous data sources.
  
• Collaborate with cross-functional teams to translate analytical and business requirements into scalable technical solutions.
  
• Maintain technical documentation, version-controlled codebases, testing workflows, and CI/CD pipelines.
  
• Contribute to system architecture, technology selection, deployment strategies, and continuous improvement of the platform.
  

Requirements

• Bachelor’s or Master’s degree in Computer Science, Software Engineering, Geo informatics, Geospatial Data Science, or a related field.
  
• 3+ years of experience in full-stack web development, preferably involving data-intensive or analytical applications.
  
• Strong proficiency in modern front-end technologies such as React, Vue.js, or Angular.
  
• Experience with data visualization and web mapping libraries such as D3.js, Leaflet, Map box GL, OpenLayers, or Deck.gl.
  
• Strong backend development experience using Node.js, Python (Flask/FastAPI/Django), Java, or equivalent technologies.
  
• Strong understanding of RESTful API design, database architecture, and data integration.
  
• Experience with relational and/or spatial databases such as PostgreSQL/PostGIS, MongoDB, or equivalent.
  
• Experience working with cloud platforms such as AWS, Azure, or GCP.
  
• Understanding of geospatial data structures and processing, including raster and vector data.
  
• Familiarity with integrating AI/ML models and analytical pipelines into production applications.
  
• Experience with real-time data integration technologies such as WebSockets, MQTT, or equivalent is an advantage.
  
• Familiarity with ETL/data engineering workflows, Docker, CI/CD, and version-control systems.
  
• Strong problem-solving, system-design, and cross-functional collaboration skills.
  

• Experience developing geospatial or data-intensive platforms.
  
• Experience working with large-scale spatial datasets and geospatial APIs.
  
• Understanding of remote sensing and Earth Observation data is an advantage.
  
• Experience deploying AI/ML or data-processing workflows through APIs or cloud infrastructure.
  
• Exposure to scalable system architecture and distributed data-processing workflows.