BUILD A DATAWAREHOUSE END TO END USING THE MODERN DATA STACK

Objective: In this workshop, we will build a data warehouse in the cloud (Snowflake) from scratch using the Medallion Architecture. We’ll cover the evolution of data architectures from traditional data normalization and data modeling to the modern data stack and learn how organizations today

leverage cloud technologies for scalable, reliable, and efficient analytics.

By the end of this course, you’ll have hands-on experience setting up a Snowflake project, implementing Bronze–Silver–Gold models, ensuring data quality with dbt and Great Expectations, and orchestrating workflows with Airflow or Dagster.

Why This Workshop Matters

Shift to the cloud: Most industries have moved away from on-premise servers to the cloud for scalability, cost efficiency, and performance.

Industry adoption of Medallion Architecture: The Medallion approach (Bronze, Silver, Gold) is the de facto standard in modern analytics engineering.

Practical application: The principles and workflows you’ll implement here mirror what’s used by data teams in real organizations today.

Prerequisites

  Vs code, python installed

ideal for data analysts who want to pivot to analytics engineers, data engineers, analytics engineers and BI developers

What you will gain

• Understand the evolution of data architectures from on-prem to the cloud.

• Learn data normalization and modeling principles as the foundation of any data warehouse.

• Explore the modern data stack and how the Medallion Architecture (Bronze, Silver, Gold) is applied in the industry.

• Gain practical experience in Snowflake setup, ETL/ELT, dbt modeling, and data quality testing.

• Learn to orchestrate workflows using Airflow or Dagster and connect to BI tools like Power BI for analytics.

• Work on a capstone project to simulate a real-world data warehousing use case.

Building a data warehouse course outline

Meet Our Trainer

Simon Ngugi is a passionate Data Engineer with extensive experience in both data engineering and analytics engineering. Over the years, he has built strong expertise in modern data technologies that are widely adopted across industries, enabling organizations to design scalable, ecient, and reliable data solutions. 

Beyond his engineering work, Simon is an enthusiastic trainer who has led numerous technical workshops and sessions. His teaching style is beginner-friendly yet comprehensive, making complex concepts in the modern data stack accessible to learners at all levels. 

Driven by his commitment to mentorship and community building, Simon founded the DATECH COMMUNITY YouTube channel, where he shares hands-on data engineering projects, practical tutorials, and guidance for aspiring data professionals.