What's inside?

Data engineers, analysts and managers with at least 1-2 years of experience that now want to learn more about strategy and design rather than just development. 

This course is not for students or junior level engineers still learning the fundamentals of data topics (SQL, databases, data types, etc.). The course assumes a certain level of experience and would likely feel too advanced for those just getting started.

This is also not for those looking for step-by-step tutorials on every tool and/or approach. 

Instead, this course covers topics and strategies at a higher level and assumes more hands-on trainings will be covered separately. 

Sure, you could probably track down most of this information somewhere on my channel or other places online.

You can find anything on the internet if you're willing to spend the time on it.

But this course does the heavy lifting of gathering that information for you while also presenting it all in a clear and organized way.

The topics covered are based both on my career as an engineer & consultant as well as many (many) hours spent trying to learn this stuff on my own over the years.

The lessons are also designed to fit the flow of course, rather than being random, unrelated videos.

In short, you don't have to take this course to learn data engineering, architecture & strategy concepts.

But it will save you a ton of time, give you a higher quality experience and leave you with bonus resources to help you going forward.

Some (but not all) of the topics we'll dive into include:

• The 3 Pillars of Data Engineering (& it's history)
• Common tools, skills & languages
• The 10 Key Modern Data Stack (MDS) Components
• Common strategies, data modeling & ways of collaborating

You'll also see how to build your own roadmap for continued learning in your career as a data engineer.

By the end, you'll feel clarity (not overwhelm) by modern data engineering, know how to put together the pieces of a modern data architecture and where you need to focus your future development.

To avoid creating an unreasonably long and unfocused learning experience, this course will not include:

1. Tutorials (no step-by-step)
2. Data Engineering for software applications (focused on internal analytics)
3. Discussing every possible option (focused on common examples & general categories)

However, you will leave with the knowledge and tools to address each of these on your own outside of the course.

In short, to learn from my experience so you can save time and effort.

I've worked on 8 data architectures in the last decade at companies ranging from Fortune 100 down to small start-ups.

I also started my own company as an independent data consultant in 2021 which has led to a lot of amazing conversations with data leaders, product managers and the data community at large.

Lastly, I have taught hundreds of thousands on YouTube (2M+ views) which has allowed me to hone my teaching style. Perhaps you found me from there!

This course consolidates all of this experience into a single, concise course for you to learn from.

If for any reason you're unsatisfied with the course, you can request a refund and get 100% of your money back. No questions asked.