reachanu21 - Overview
Anu — Data Engineering + AI Engineering Portfolio
A collection of my hands-on projects in Data Engineering and AI Engineering.
I specialize in Azure, Microsoft Fabric, Snowflake, and applied LLM-based systems.
Tech Stack
Data Engineering
Azure Synapse • Azure Data Factory (ADF) • Microsoft Fabric • Snowflake • SQL • Python • PySpark • Pandas • ETL/ELT • Data Modeling • Data Warehousing
Streaming
Azure Event Hub • Fabric Eventstreams
AI Engineering
LLMs • RAG • Embeddings • Vector Databases • FAISS • Multi-Agent Systems • Copilot Studio • Streamlit • Ollama • Prompt Engineering • LLM Orchestration
Projects
1. Multi-Agent AI System (Mentora, Nexa, Kanu)
Tech: Python, Streamlit, LLMs, RAG, Vector DB
Description:
A multi-agent architecture where each agent has a specialized role and collaborates to solve tasks.
Features:
- Agent-to-agent communication
- Retrieval-Augmented Generation (RAG) for knowledge retrieval
- Streamlit UI for interaction
- Modular orchestration for future expansion
2. RAG Pipeline for Enterprise Knowledge Retrieval
Tech: Python, FAISS, Embeddings, Azure Storage
Description:
A full RAG pipeline that ingests documents, generates embeddings, stores them in a vector database, and retrieves context for LLM responses.
Features:
- Document chunking and embedding generation
- FAISS-based vector search
- Context injection into LLM prompts
- Simple UI for querying
3. Azure Synapse + ADF Pipelines
Tech: Azure Synapse, Azure Data Factory, SQL
Description:
Enterprise-grade ETL/ELT pipelines with parameterization, monitoring, and reusable components.
Highlights:
- Parameterized pipelines for reuse
- Orchestration of batch data flows
- Data quality checks and monitoring
4. Real-Time Streaming with Event Hub + Fabric Eventstreams
Tech: Azure Event Hub, Fabric Eventstreams
Description:
Real-time ingestion and processing for high-volume operational data.
Highlights:
- Event Hub ingestion and consumer groups
- Fabric Eventstreams for unified streaming
- Near real-time analytics integration
5. Snowflake Data Modeling and Optimization
Tech: Snowflake, SQL
Description:
Designed fact/dimension models, optimized warehouses, and built performance-tuned SQL transformations.
Highlights:
- Schema design for analytics
- Query performance optimization
- Data validation and quality checks
Contact
- LinkedIn: [Your LinkedIn URL]
- GitHub: [Your GitHub URL]
- Email: [Your Email]