Full Stack Developer
Agrosat
Overview
At Agrosat, I worked on building agricultural analytics platforms that processed massive amounts of satellite imagery data to provide farmers and agronomists with actionable insights about crop health, irrigation needs, and field conditions.
The role involved handling large-scale data processing, building interactive dashboards, and creating visualizations that made complex agricultural data accessible and actionable for non-technical users.
Key Projects & Features
Satellite Data Processing
Built pipelines to process and analyze 100GB+ of satellite imagery data for agricultural insights
Interactive Dashboards
Developed real-time analytics dashboards with custom visualizations for crop monitoring
API Development
Created RESTful APIs for data access, processing, and third-party integrations
Data Visualization
Implemented advanced charting and mapping solutions using D3.js for geographic data
Performance Optimization
Optimized database queries and implemented caching strategies for large datasets
Cloud Infrastructure
Set up AWS infrastructure for data storage, processing, and application hosting
Key Achievements
- ▸Processed and analyzed 100GB+ of satellite imagery data
- ▸Built responsive dashboards handling real-time agricultural metrics
- ▸Optimized data queries reducing load time by 60%
- ▸Implemented caching layer with Redis for frequently accessed data
- ▸Developed custom map visualizations for geographic crop analysis
- ▸Created automated data ingestion pipelines from satellite sources
- ▸Collaborated with agronomists to translate data into actionable insights
Technologies Used
Technical Challenges Solved
Large Data Handling
Implemented efficient data processing pipelines to handle 100GB+ of satellite imagery. Used chunking strategies and background jobs to process data without blocking the application.
Performance Optimization
Reduced dashboard load times by 60% through database query optimization, implementing Redis caching for frequently accessed data, and using pagination for large datasets.
Data Visualization
Created custom map visualizations using D3.js to display geographic crop data with color-coded health indicators, allowing farmers to identify problem areas quickly.
Cloud Infrastructure
Set up AWS S3 for efficient satellite data storage and implemented automated data ingestion pipelines that processed new imagery daily.
Impact
The dashboards and analytics tools I built helped farmers and agronomists make data-driven decisions about irrigation, pest control, and harvest timing. The platform processed data for thousands of hectares of farmland, contributing to more efficient water usage and improved crop yields.