Cracking the Data Engineering Interview: Land your dream job with the help of resume-building tips, over 100 mock questions, and a unique portfolio

"Cracking the Data Engineering Interview" is an invaluable resource for anyone aspiring to land a dream job in data engineering. This comprehensive guide provides a clear roadmap to mastering the essentials of data engineering and excelling in interviews.Key Features:The book excels in helping you develop your personal brand and portfolio, making you stand out in the competitive job market. It offers a quick refresher on core topics like Python, SQL, ETL, and data modeling, ensuring you're well-prepared for both technical and behavioral interview rounds. The inclusion of over 100 mock questions provides extensive practice, boosting your confidence and readiness.Book Description:Preparing for data engineering interviews can be daunting due to the plethora of tools and technologies. This hands-on guide simplifies the process by focusing on foundational and advanced knowledge. It starts with an overview of data engineering roles and progresses to practical tips on resume building, networking, and salary negotiation. The book covers essential topics such as data modeling, ETL processes, cloud computing, big data, and machine learning. Additionally, it delves into CI/CD, data security, and privacy, offering a holistic view of the field.What You Will Learn:By the end of this book, you'll understand how to create maintainable and scalable code, master core data engineering tasks, and prepare for a wide range of interview questions. It also guides you in building your personal brand to stand out as a candidate.Who This Book Is For:This book is perfect for aspiring data engineers looking for comprehensive guidance on landing and excelling in data engineering interviews. A basic understanding of data engineering concepts is required.Conclusion:"Cracking the Data Engineering Interview" is an outstanding guide that combines expert advice, practical tips, and real-world insights. It's an essential read for anyone serious about pursuing a career in data engineering. Highly recommended!

TL;DR: - Pretty good for overview of DE knowledge domains, pretty useless for actual interviews - Good for noobs who need a (very very) general overview of what to master in DE - Little to no value for DEs or really anyone willing to search online and track down what is ultimately freely available, plentiful information***There is nothing in this book that is not freely available online***:SQL interview questions, "unique" portfolio construction guides, database design principles, etc. At ~150 pages, you will in fact find much more detailed treatments of these topics through your favorite search engines if you have the time and grit (ok, maybe just the time ;) ).The value of this book lies in ***aggregating a wide range of DE topics in one place with a bird's-eye view*** to help you not get lost in the details (and DE has details aplenty). It does this by presenting "essentials" for all the major areas of DE as well as some practical fundamentals related to applying to jobs and interviewing. You can then take any given "essential" and drill down through more (serious) study and practice through free or cheap online sources. If you're new to DE, you need to build stuff, bottom line.This may not seem like much of a value-add, but for anyone even slightly familiar with DE, there is a vast domain of knowledge and detail to stay abreast of, and acquiring a good mental model of the domains and their interrelations can be useful for those who are just starting out as well as those who could benefit from some refinement to their working conceptualizations (though I'm highly skeptical of the latter, and would instead recommend "Fundamentals of Data Engineering" by Reis & Housley).All in all, this book serves as a roadmap. It therefore appears to target mainly people wanting to get into the field of DE. If you're part of that group, be careful: pretty much anything in tech knowledge-wise is freely available so always consider what it is you're actually paying for when looking at resources.I'm skeptical that anyone with even a little experience in DE could justify the cost of this book.Packt books are hit and miss - sometimes excellent, sometimes not so much. This title fits in the category of "let's make money off of people who are entering <tech_field> because they don't know any better". Approaching DE from a software engineering background, I bought the book thinking it would be more practically useful for interviews (sort of like the classic "Cracking the Coding Interview" by McDowell whose title it riffs off of) but it largely FAILS IN THIS AREA.A better title would be "Roadmap for Data Engineering".

This comprehensive guide on Preparing for Data Engineering Interviews delves into the fundamental responsibilities of a data engineer. Ideal for those transitioning from an ETL developer role to a more in-depth position as a data engineer, this book proves highly beneficial. It not only provides insights into the intricacies of the role but also offers guidance on constructing a professional portfolio on LinkedIn and expanding your professional network. Additionally, the book equips you with a range of general data engineering interview questions, enhancing your preparation for the interview process.

"Cracking the Data Engineering Interview" serves as an invaluable compass for those navigating the complexities of data engineering interviews. With a focus on building a strong personal brand and portfolio, this guide offers expert assistance to stand out during interviews. The book covers core data engineering topics like Python, SQL, ETL, and data modeling, providing a quick refresher and 50 mock questions to master both technical and behavioral rounds.This hands-on approach simplifies the learning journey, offering insights into resume building, cover letter writing, and effective networking. From data processing and ETL to data security and privacy, the book provides a holistic view, preparing readers for the nuances of the role. By the end, armed with over 100 interview questions, aspiring data engineers will be well-prepared to crack the interview process and secure their dream roles.