Data Engineering with AWS: Acquire the skills to design and build AWS-based data transformation pipelines like a pro

I have been awestruck by the way Gareth gets his work done, the simplest of ways to get complex stuff published, he is a genius and I will rely on him to lover complexity to a completely new level!

Great book, but knocking a star off for production errors in some of the images (some icons are missing).

As an aspiring Data Engineer, navigating through the myriad concepts and technologies is a daunting task. In the realm of modern Data Engineering, the cloud is undeniably a linchpin. It was precisely this emphasis on cloud-centric knowledge that drew me to Gareth Eagar's book, and having perused the reviews of the first edition, my conviction in its high-quality content was cemented.I found my expectations to be well-founded; the book seamlessly blends high-quality conceptual information with hands-on activities. It serves as an invaluable resource, offering a comprehensive guide to understanding the intricacies of data engineering in the era of cloud computing. The content not only equips me with the requisite knowledge but also provides practical insights through hands-on exercises.This book is more than just a learning tool; it's a roadmap that propels aspiring Data Engineers into a competitive stance within the dynamic Data Engineering market. Gareth Eagar's meticulous approach not only lays the groundwork for my future career but also positions me for success in obtaining the coveted AWS Data Engineer certification.I extend my gratitude to Gareth Eagar for crafting such an impactful resource. The dedication poured into this book is palpable, evident in the seamless flow of content and hands-on activities. The clarity with which concepts are elucidated has bridged the gaps in my understanding, making this book an indispensable companion in my journey to mastering Data Engineering with AWS."

First time I've even written a review for a book on Amazon. That's how good this book is. Gives you enough theory with practical examples, use cases and hands-on experience in AWS.