You already know how to build software. This workshop shows you how to apply that engineering mindset to data.

Designed for software engineers who are curious about data engineering, this hands-on session introduces the core building blocks of modern analytics engineering and DataOps, with dbt as the centerpiece. We’ll start with the big picture — how raw application data becomes trustworthy, usable datasets — then work through the practices that make data systems maintainable: modeling, testing, documentation, version control, code review, deployment, and observability.

Along the way, we’ll compare familiar software concepts to their data equivalents: services vs. pipelines, CI/CD vs. DataOps, unit tests vs. data quality tests, and application schemas vs. analytics models. You’ll see where software engineering instincts help, where they need to adapt, and why dbt has become such a powerful tool for bringing software-style discipline to the data stack.

By the end of the workshop, attendees will have:

* a practical mental model of modern data engineering and analytics engineering
* hands-on experience building and testing transformations with dbt
* an introduction to DataOps concepts and workflows
* a clearer understanding of how software engineering skills transfer into data work

Whether you’re exploring a move into data engineering, collaborating more closely with data teams, or just want to understand what happens after the database write, this workshop will give you a grounded, practical way in.