Gen AI Project 5: AI-Powered ETL Agents with DataSense

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.