Foundational Analytics Engineering

Learn the fundamentals of modern analytics engineering. Build reliable data models, structure transformations, and apply best practices used by high-performing data teams.
Length & format

2-day instructor-led training (virtual or on-site)

Why take this course?

Learn how modern data teams build reliable, production-ready analytics models and workflows using dbt.

Who is this for?

For data analysts, analytics engineers, and data engineers who want to get hands-on with modern analytics engineering practices and data modeling.

What is expected from you?

You should be comfortable writing SQL queries, including SELECT, JOIN, WHERE and GROUP BY statements. Everything else you’ll learn in the course.

What you will learn?

  • Build clean, modular analytics models from raw data to business-ready datasets
  • Apply structured design patterns for scalable and maintainable analytics projects
  • Use templating and reusable logic to simplify complex SQL transformations
  • Implement data quality tests and documentation from day one
  • Deploy analytics models to production using modern analytics engineering workflows used by high-performing data teams
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Build the skills your data team needs to adopt and scale modern analytics and AI-native workflows.
Our experts design and deliver training tailored to your data platform, architecture and use cases.

Hands-on learning

Work through realistic labs and exercises based on modern data team workflows and production environments.

Learn from experts

Our instructors are analytics practitioners who build and run production data platforms.

Built for modern data teams

Learn the practices behind scalable analytics engineering and AI-native data workflows used by leading organizations.

Meet your trainers

Simo Tumelius

Co-founder, Lead instructor
Started in software engineering, where test-driven development and clean code shaped his approach.
Then transitioned into data, focusing on making analytics systems scalable, tested, and reliable.
Simo discovered dbt in 2019 and recognized its potential early on.
In early 2021, he went full-time freelance, helped teams adopt dbt and build sustainable analytics practices through mentoring, coaching, and training.
He has taught teams across Europe, the U.S., and India, with focus on helping people truly understand and confidently use modern data tools.
His training materials, built over five years, now form the foundation of Breakout Labs' dbt Foundational and Advanced Analytics Engineering programs

Miguel Carvalho

DATA Engineer, instructor
Started in software engineering before moving into data engineering, where he focuses on building reliable and well-structured data platforms.
Has worked across consulting, small companies, and now at a large tech company, giving him experience working in very different data environments.
He works extensively with Snowflake, dbt, and modern ELT tools to design and maintain production-grade pipelines, with a strong focus on consistent metrics and clean, scalable data models.
Alongside his hands-on work, Miguel delivers training in Foundational and Advanced Analytics Engineering, with an emphasis on practical approaches that teams can adopt straight away.
His focus is on helping teams build confidence and autonomy in their data stack.