In this episode, we dive into one of the biggest challenges in data engineering and data warehousing—team sizes. Should a team be as small as two people, or do you need a large group to get the job done? We discuss:

- The impact of team size on productivity

- The role of automation in reducing workload

- Why some projects slow down despite large budgets

- The importance of skill distribution within a team

- How onboarding and documentation affect efficiency

🚀 Whether you're running a data warehouse or managing a data engineering project, this episode will help you rethink your approach to team structure and tooling.

📌 Chapters:

00:00 – Introduction

00:12 – The challenge of team size variation

00:52 – Do large teams slow projects down?

01:49 – Automation vs. manual coding: The real cost

02:43 – The essential skills for a data team

03:44 – Finding the ideal team size

05:00 – The problem with unnecessary manual work

06:16 – Why throwing more people at a problem doesn’t help

07:06 – Key takeaways for optimizing data teams

08:11 – Outro & next steps

🔗 Check out our resources and links in the description to continue your learning journey!