Building Scalable Data Platforms on GCP

Most data platforms don’t fail because of bad code — they fail because of bad structure.
In this talk, we will look beyond pipelines to explore what truly makes a data platform
sustainable on Google Cloud Platform (GCP). Drawing on real-world projects, we’ll discuss
how ownership, Infrastructure as Code (IaC), environment isolation, and governance shape
the long-term reliability and scalability of data systems.
You’ll see how platform thinking — layering ingestion, processing, and serving — helps
teams reduce duplication, clarify responsibilities, and evolve their architecture as the
organization grows. The session blends practical design choices with lessons learned from
multiple GCP implementations, offering a realistic path from “just pipelines” to “platforms that
scale and last.”

Vorkenntnisse

This talk is ideal for Beginner Data Engineers, BI professionals, and Developers looking to optimize data workflows in a cloud-native environment using modern ELT techniques.

Lernziele

By the end of this session, attendees will:

• Understand the key structural pitfalls that cause data platforms to degrade over time.
  
• Learn how to design clear ownership, environment, and IaC boundaries on GCP.
  
• See how layering ingestion, processing, and serving leads to more maintainable architectures.
  
• Discover patterns for scalable governance and automation in modern data platforms.
  
• Take away actionable lessons for evolving from data pipelines to platform architecture thinking.