I'm a B.Tech Artificial Intelligence graduate focused on Data Engineering and building reliable data pipelines.
My core stack includes Python, SQL, PySpark, AWS, Apache Airflow, Docker, and Snowflake.
I'm interested in data processing, cloud data engineering, data warehousing, pipeline orchestration, and scalable data systems.
┌──────────────┐
│ Data Sources │
└──────┬───────┘
↓
┌──────────────┐
│ Ingestion │
└──────┬───────┘
↓
┌──────────────┐
│ Processing │
│ PySpark │
└──────┬───────┘
↓
┌──────────────┐
│Transformation│
└──────┬───────┘
↓
┌──────────────┐
│ Storage │
│ Snowflake │
└──────┬───────┘
↓
┌──────────────┐
│ Analytics │
└──────────────┘
- 🔄 Build ETL / ELT data pipelines
- ⚡ Work with PySpark for data processing
- ☁️ Build pipelines using AWS data services
- 🗄️ Work with Snowflake and SQL for analytical workloads
- 🔄 Orchestrate workflows using Apache Airflow
- 🐳 Use Docker for containerized environments
- 🧹 Work with structured and semi-structured data
- ⚡ PySpark & distributed data processing
- ☁️ AWS Data Engineering
- 🗄️ Snowflake & Data Warehousing
- 🔄 Airflow & pipeline orchestration
- 🏗️ Data pipeline architecture
- 📈 Scalable data processing
- 🤖 Data Engineering for AI systems
With a background in Artificial Intelligence, I'm also interested in how data engineering supports modern AI systems.
Raw Data
│
▼
Data Engineering
│
Clean & Reliable
│
▼
AI Systems
My interest is particularly around data pipelines, data quality, large-scale processing, and the data infrastructure behind AI applications.
Building my career as a Data Engineer and growing toward designing scalable, reliable, and production-ready data platforms.
