UI/UX  →  API  →  Database  →  ETL/ELT Pipeline  →  Data Warehouse  →  Dashboard

6+ years building across the full stack. I don't just write features, i design systems and take them to production. Whether it's a React frontend consuming a GraphQL API, a FastAPI service with Redis caching, or a Medallion pipeline landing clean data into Snowflake for Power BI.

I design and maintain end-to-end ELT pipelines following Medallion Architecture with Kimball dimensional modeling:

Raw Sources
     │
     ▼
┌─────────────┐
│ Bronze Layer │  ──  Raw ingestion, no transformations
└─────────────┘
     │
     ▼
┌─────────────┐
│ Silver Layer │  ──  Cleaning, validation, joins
└─────────────┘
     │
     ▼
┌─────────────┐
│  Gold Layer  │  ──  Star Schema · Fact + Dimension tables
└─────────────┘
     │
     ▼
┌─────────────┐
│  Snowflake   │  ──  Cloud-native warehouse · incremental loads
└─────────────┘
     │
     ▼
┌─────────────┐
│   Power BI   │  ──  Dashboards connected directly to the warehouse
└─────────────┘

I build Retrieval-Augmented Generation (RAG) systems that connect LLMs to real data sources — giving AI responses grounded in actual business context rather than hallucinations.

User query
    │
    ▼
[ Embedding Model ]  →  Vector similarity search
    │
    ▼
[ Retrieved context ]  →  Injected into LLM prompt
    │
    ▼
[ LLM Response ]  →  Accurate · grounded · useful

• 📚 Working through AWS Cloud Practitioner → AWS Data Engineer Associate (DEA-C01)
• 🔬 Deepening expertise in Snowflake + dbt + Power BI production pipelines
• 🤖 Exploring RAG architectures and LLM integrations in real products
• 🌍 Open to remote roles in Senior Full Stack or Analytics Engineering