Designing production-grade data platforms from real-world constraints.
Join my structured masterclass for engineers and tech leads
who need to make platform decisions with real cost and revenue impact.
This is not a course about tools or certifications.
It is a decision-focused masterclass on how to design data platforms that avoid costly mistakes and enable business growth.
COMING APRIL 2026
Who this is for
This masterclass is for you if you:
- work on real data platforms in production
- are responsible for architectural or platform decisions
- want to reduce cloud costs and operational risk
- need to justify technical decisions to stakeholders
- are moving from a traditional data platform to a more modern architecture
- already know the tools, but struggle with trade-offs and priorities
Not a good fit if you:
- are just starting in data engineering
- are looking for tool tutorials or certifications
What you will learn
- Analyzing business requirements and technical constraints before choosing tools
- Identifying decisions that drive unnecessary cost and complexity
- Designing platforms that scale with the business instead of blocking it
- Connecting architecture decisions to cost, reliability, and revenue impact
- Applying a reusable decision framework across projects
Format
- Runs over multiple weeks with a clear structure
- Focus on decisions, trade-offs, and architectural reasoning
- No live coding, no setup sessions, no tool deep dives
- Designed to fit alongside a full-time job
Hands-on case
You will work through a realistic, non-ideal platform case
based on a growing company with legacy decisions and business pressure.
No greenfield examples. No perfect architectures. Only real-world trade-offs.
Why this masterclass is different
Most training focuses on how to use tools.
This masterclass focuses on when, why, and whether you should use them at all.
The goal is not more knowledge.
The goal is better decisions with measurable business impact.
Outcome
After completing the masterclass, you will be able to:
- explain and defend platform decisions with confidence
- avoid expensive architectural mistakes before they happen
- design platforms that support growth instead of slowing it down
- reuse the same decision framework across teams and projects