Fullstack Engineer with 2+ years in Geospatial Data Processing & AI/ML Development
AI is analyzing your overall score…
Identifying your key strengths…
Evaluating your skill match against the job requirements…
Assessing your cultural and operational fit
Software Engineer with 2+ years of experience in geospatial data processing and full-stack development at ISRO Space Applications Centre. Expert in building CNN-based deep learning pipelines, real-time monitoring dashboards, satellite data processing systems, and Agentic AI layers for intelligent geospatial automation. Proficient in Python, JavaScript, Vue.js, PyTorch, and PostgreSQL with a proven track record of deploying scalable solutions handling 500GB+ datasets across 15+ Indian states.
Dharmsinh Desai University
Master of Technology · Computer Engineering
August 1, 2022 – June 30, 2024
Shri S'ad Vidya Mandal Institute of Technology
Bachelor of Engineering · Information Technology
August 1, 2018 – June 30, 2022
ISRO Space Applications Centre (SAC)
Software Engineer
September 1, 2024 – Present
Ahmedabad, Gujarat, India
ISRO Space Applications Centre (SAC)
Research Intern
June 1, 2023 – April 1, 2024
Ahmedabad, Gujarat, India
Satellite Data Download and Status Monitoring System
January 1, 2024 – Present
Engineered automated pipeline for Sentinel-1, Sentinel-2, and AWiFS data from ESA Copernicus and ISRO MOSDAC processing 50GB+ daily with 99%+ uptime. Built Django backend with multi-threaded downloads (10+ concurrent streams), MD5 validation, and NetCDF-to-GeoTIFF conversions using GDAL. Created Vue.js dashboard with OpenLayers mapping displaying tile-wise coverage, status tables, database verification, and color-coded visualization.
Real Estate Property Listing Platform
January 1, 2024 – Present
Built full-stack web platform with user authentication, geospatial property search using Leaflet maps, and price trend analytics with historical data visualization.
Multi-Application Monitoring and Health Dashboard
January 1, 2024 – Present
Deployed enterprise-grade monitoring system for 20+ applications and 15+ Linux servers with 5-second refresh intervals featuring CPU, memory, disk, and network tracking. Implemented automated email and SMS alerts, predictive forecasting models, and custom Python monitoring agents with less than 1% CPU overhead.
Heart Disease Prediction Model
January 1, 2024 – Present
Trained classification models achieving 92% accuracy through feature engineering and hyperparameter tuning; deployed as Flask REST API for healthcare applications.
Geoentity Data Export Tool Dashboard
January 1, 2024 – Present
Developed interactive geospatial data extraction tool with administrative boundary selection (state, district, and taluk levels) supporting multi-format exports (CSV, GeoJSON, Shapefile) with batch processing and email notifications.
Vedas MIS – Unified Monitoring Hub
January 1, 2024 – Present
Developed centralized monitoring hub integrating 9+ specialized applications via iframe architecture including Server Monitor, Service Monitor, Processing Script Monitor, Data Chain Monitoring, Publish Monitoring, Ridam Pool Analytics, Pool Group Health, Geoentity Monitoring, and Team Analytics. Implemented real-time alert aggregation using WebSockets providing single-pane-of-glass visibility for SAC operations consolidating infrastructure monitoring, satellite data pipelines, and team analytics.
Cultural Fit Analysis
The candidate's project portfolio demonstrates a strong alignment with roles requiring both deep technical expertise and practical application, especially in data-intensive and full-stack environments. Their work at ISRO SAC on projects like national agricultural monitoring and flood alerts indicates a commitment to impactful work and an ability to handle large-scale, critical systems. The diversity of projects, from satellite data processing to AI-driven GIS dashboards and real estate platforms, shows adaptability and a broad interest in applying technical skills across different domains. This breadth of experience, combined with a focus on open-source tools and real-time systems, suggests a good cultural fit for an innovative and results-driven team.
Soft Skills & Operational Fit
The candidate's project descriptions indicate strong problem-solving skills, particularly in handling complex geospatial data challenges and building robust monitoring systems. The emphasis on '99%+ uptime' and 'less than 1% CPU overhead' suggests an operational mindset focused on efficiency and reliability. Their work at ISRO SAC implies an ability to work in high-stakes, data-intensive environments and contribute to critical national projects. The detailed descriptions of implementing automated pipelines and real-time alerts also point to a proactive and detail-oriented approach.