Designed and composed a modular RBAC system in Python/Django, enabling permission control for 15+ user roles and 50+ internal modules, securing access for 7K+ users.

Built a unified notification engine using Kafka, Redis, and websockets to deliver 5K+ daily alerts; integrated Celery and Django email module for reliable email delivery, reducing user follow-ups by 40%.

Engineered a scalable data ingestion system using Python cron jobs on AWS ECS to collect 1M+ records/day from 7 ad platforms; Reduced processing time from 4.5 h to 45 min using parallel processing and batching, and enabled live dashboard updates via WebSockets to reflect refreshed data in 20 to 45 seconds.

Established data sync triggered by logging-in and on demand using Celery and Redis, improving the freshness of the dashboard data by 70%.

Introduced a 2-hour cooldown mechanism using Redis TTL to prevent redundant data fetches, eliminating unnecessary API calls.

Built interactive crop planning dashboards using React.js and Django REST Framework, enabling 100+ farmers to create and save seasonal crop cycles.

Developed a yield optimization engine in Python to recommend high-yield crop strategies, increasing optimal plan adoption by 40%.

Implemented JWT authentication and compliance-ready data tracking, integrating third-party government APIs to securely report crop cultivation, yield, and sales for regulatory compliance.