Gen AI Project 5: AI-Powered ETL Agents
In this hands-on, 3-hour advanced project workshop, you will build a production-style AI Agent powered ETL and File Migration Platform that automatically transfers data from Snowflake to Google Cloud Storage using React, FastAPI, LangChain, and LLM-driven agents.
This is not a demo. This is how modern enterprises are beginning to design autonomous data pipelines.
Instead of writing static ETL scripts, you will design an AI-orchestrated migration system where agents can:
• Understand natural language
• Inspect cloud storage
• Decide what to move
• Handle versioning
• Resolve conflicts
• Track progress
• And automate the entire workflow
All through a chat-driven UI and intelligent backend orchestration.
What You Will Build
A full-stack AI Data Migration Platform with:
🔹 Intelligent ETL via Agents
• LLM-based agent that plans migration steps
• Tool-calling to Snowflake and GCS
• Context-aware decision making
• Automated version control and cleanup
• Error handling and retry logic
🔹 Production-Grade Architecture
• React dashboard with chat interface
• FastAPI backend with async pipelines
• LangChain agent with tool routing
• Snowflake stage integration
• Google Cloud Storage sync
• Real-time status tracking
🔹 Functional Capabilities
• List, download, upload, rename, version, delete files
• One-click full sync
• Conflict-aware versioning
• Workspace based staging
• Natural language control:
“Move only the latest reports to GCS”
“Sync everything except CSVs”
“Re-upload failed files”
🔹 Enterprise Design Thinking
• Agent workspace pattern
• Tool registry pattern
• Secure credential handling
• API driven orchestration
• Extensible multi-cloud roadmap
Why This Project Matters
This project teaches you how ETL will be built in the Agentic Era.
Not with:
• Cron jobs
• Bash scripts
• Static DAGs
But with:
• Planning agents
• Reasoning layers
• Tool-driven execution
• Autonomous recovery
• Conversational operations
You will understand how:
• AI replaces traditional orchestration logic
• Agents become the control plane of data platforms
• LLMs coordinate cloud services
• Modern RAG + ETL + Automation converge
Who Should Attend
Perfect for:
• Data Engineers
• Analytics Engineers
• AI Engineers
• Cloud Architects
• Platform Engineers
• GenAI Developers
• ETL / Pipeline Developers
• Anyone building production AI systems
Prerequisite:
Basic Python + API familiarity. No deep React required.
What You Will Learn
• How to design Agent-Orchestrated ETL
• How LangChain tool routing works in real systems
• How to combine UI + Agents + Cloud APIs
• How to build multi-step autonomous workflows
• How to architect LLM-controlled data pipelines
• How to move from script-based ETL to Agent-based ETL
Outcome
After this session, you will walk away with:
✔ A complete working AI Data Migration Platform
✔ A real enterprise-style GenAI project for your resume
✔ Deep understanding of Agentic ETL Architecture
✔ A reusable foundation for building AI Ops, DataOps, MLOps agents
✔ Confidence to design LLM-orchestrated cloud systems
This is Gen AI Project 5 - where LLMs stop chatting and start running your data platform.