S2E6 – Stop Scaling What You Don’t Understand With John Napoleon-Kuofie

Rebuilding Trust in Your Data Stack – Why Monzo Hit Pause Before Scaling

What happens when you inherit a data platform that’s grown too fast? For John Napoleon-Kuofie, Analytics Engineer at Monzo, the answer was clear: stop, simplify, and rebuild with purpose.

In this episode, John shares how his team is tackling legacy bloat, test fatigue, and the pressure to scale, while keeping trust and clarity at the heart of every decision.

👉 How do you deliver reliable insights when your models number in the thousands and no one knows where they came from?

What you’ll learn:

✅ How Monzo is redefining core concepts like “payment” to simplify their DBT estate
✅ Why default test patterns create more noise than value, and what to do instead
✅ The risk of scaling fast without understanding what you’ve inherited
✅ Why clean joins and clear abstractions matter more than AI
✅ How a culture of bottom-up innovation helps Monzo stay agile

This episode is essential listening for data engineers, analytics leads, and platform owners who want to build systems that last, without sacrificing clarity, accountability, or team sanity.

Watch the full episode on YouTube, or listen on Spotify and Apple Podcasts.

👤 John Napoleon-Kuofie on LinkedIn
👤 Aaron Phethean on LinkedIn
🎧 Data Matas Podcast
📺 YouTube
🌐 Matatika Website