Data Pipelines • Distributed Computing • Cloud Infrastructure • Real-time Analytics
Apache Spark |
Apache Kafka |
Python |
Airflow |
Snowflake |
AWS |
GCP |
Docker |
Kubernetes |
Terraform |
React • Node.js • Microservices • TypeScript • Real-time Systems
TypeScript |
React |
Next.js |
NestJS |
PostgreSQL |
| Project | Stack | Impact | Status |
|---|---|---|---|
| Real-time Financial Analytics Platform | Spark, Kafka, Airflow, Snowflake | Processed 10TB+ daily transactions with <100ms latency | 🟢 Production |
| Healthcare ETL Orchestration | Python, dbt, PostgreSQL, Docker | Reduced data processing time by 70% for 50+ hospitals | 🟢 Production |
| Enterprise Dashboard SaaS | Next.js 14, FastAPI, Redis, Docker | Microservices with real-time WebSocket updates | 🟡 Beta |
| IoT Sensor Data Pipeline | AWS Lambda, Kinesis, S3, Redshift | Handled 1M+ events/sec with 99.99% uptime | 🟢 Production |
| AI-Powered Analytics Platform | React, Node.js, Python ML, PostgreSQL | JWT auth, RBAC, advanced visualization | 🟡 Beta |
Daily Data Processed: 15-25 TB • System Availability: 99.95% • API Response: <50ms p95
SCALABILITY FIRST → Design for 10x current load
OBSERVABILITY DRIVEN → Metrics, logs, traces in all systems
INFRASTRUCTURE AS CODE → Reproducible, versioned environments
DATA QUALITY AS FEATURE → Validation at every pipeline stage
SECURITY BY DESIGN → Zero-trust, defense in depth architecture
