Apache Iceberg Deep Dive

Learn how to build scalable, reliable, and queryable data lakes using Apache Iceberg — a powerful open table format designed for modern analytics. Through hands-on labs and real-world challenges, you’ll explore how Iceberg enables schema evolution, time travel, streaming ingestion, and more. Ideal for data engineers, platform teams, and anyone working with data lakes or Data Mesh architectures.

In this full-day, hands-on workshop, you’ll dive deep into Apache Iceberg — a high-performance table format that brings ACID transactions, schema evolution, and time-travel capabilities to cloud data lakes. Iceberg bridges the gap between batch and streaming by allowing data to be ingested from multiple engines, such as Flink or Spark, and then queried from Trino, Hive, or Dremio with confidence.

We’ll begin by understanding where Iceberg fits into modern data architecture and why traditional Hive-style tables fall short. You’ll learn how Iceberg defends your data using snapshot-based versioning and metadata-driven optimizations. Then, you’ll build a full mini lakehouse setup using Docker Compose, complete with MinIO (S3-compatible), Flink, and Trino.

About Daniel Hinojosa

Daniel is a programmer, consultant, instructor, speaker, and recent author. With over 20 years of experience, he does work for private, educational, and government institutions. He is also currently a speaker for No Fluff Just Stuff tour. Daniel loves JVM languages like Java, Groovy, and Scala; but also dabbles with non JVM languages like Haskell, Ruby, Python, LISP, C, C++. He is an avid Pomodoro Technique Practitioner and makes every attempt to learn a new programming language every year. For downtime, he enjoys reading, swimming, Legos, football, and barbecuing.

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