From Open Lakehouse to Agentic Data Platforms on AWS

Blueprints, patterns, and real-world lessons for building faster, governing better, and scaling with confidence.

Join an afternoon of practical, engineering-first sessions on building an open data lakehouse on AWS and applying agentic AI to modern data work. Learn how Apache Iceberg, AWS-native catalogs and engines, and enterprise governance fit together in production — and how AI agents can accelerate data engineering, platform delivery, and natural-language access to your entire data ecosystem. Leave with architectures, patterns, and “what actually works” takeaways you can use immediately.

Who should attend:

The event is designed for:

• CTO/Head of Data/Engineering Managers planning platform modernization and productivity gains
  
  
• Data Architects & Tech Leads responsible for scalability, cost, performance, and governance
  
  
• Data Engineers & Analytics Engineers working with pipelines, dbt, orchestration, testing, and data quality
  
  
• Data Platform / DataOps / Cloud Engineers building or migrating lakehouse and warehouse architectures on AWS
  
  
• AI/ML Engineers & Applied AI teams building RAG, vector search, Document AI, and enterprise agents
  
  

What you'll learn:

• A pragmatic reference architecture for an open lakehouse on AWS (Iceberg + Glue + multi-engine compute)

• Patterns for governance, cataloging, and operationalizing at enterprise scale

• How to integrate AI into data engineering workflows (dbt, tests, profiling, orchestration)
  
  
• A clear, implementable architecture for enterprise conversational data agents
  
  
• Practical ways to start agentic platform engineering in your team this quarter

Speakers:

	Radosław Szmit Data Architect, Xebia
	Yassir Jafar Senior Solution Architect, AWS

Agenda:

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