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Location
In office (Bengaluru)
Seniority
Middle · 3+ years exp
Employment
Full-Time

Confirmed on the employer's own hiring board on Oct 6, 2026. First seen by Alion on Oct 3, 2026.

Overview
Company
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Profile match
GalaxEye Space develops satellites combining radar and optical imaging in one payload. The fused data provides all-weather earth observation for defence and agriculture. The company was founded by graduates of a national technology institute.

We are seeking a highly skilled Full Stack Developer to design, develop, and maintain scalable web applications, platforms, dashboards, and decision-support systems that integrate geospatial data, AI-driven analytics, and real-time data sources.

The role involves working closely with software, GIS, data science, and remote sensing teams to build data-intensive applications and enable the visualization, processing, and delivery of complex spatial and analytical datasets.

Key Responsibilities:

  • 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.

Preferred Experience

  • 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.
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