Interview with Gareth Eager Author Of Data Engineering With AWS

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Q: What are your specialty areas?

Gareth: Data Analytics, with a focus on building data lakes and data platforms

Q: How did you become an author for Packt? Tell us about your journey. What was your motivation for writing this book?

Gareth: For a long time now I’ve thought about sharing my knowledge by writing a book, so when Reshma Raman reached out to me to see if I’d be interested in writing a book on data engineering on AWS, I jumped at the chance. I’m passionate about the topic of big data and how data lakes / platforms can enable an organization to democratize data and gain new insights..

Q: What kind of research did you do, and how long did you spend researching before beginning the book?

Gareth: I read up about other people’s experiences in writing tech books, and also spoke to a friend of mine that previously worked with Packt to write a book. The Packt team was great in helping to layout a good process for developing the outline of the book, and then it was just down to the hard work of taking my existing knowledge, and enhancing that with finer detail from online research (blogs, videos, product documentation, etc).

Q: Did you face any challenges during the writing process? How did you overcome them?

Gareth: I originally was going to write the book with a co-author, but unfortunately they had to drop out of the project, so that meant I was taking on the book solo, which I had not originally intended to do! Ultimately it meant it took a lot longer to complete the book, but I (mostly) enjoyed the process!

Q. What’s your take on the technologies discussed in the book? Where do you see these technologies heading in the future?

Gareth: The volume, velocity, and variety of data that organizations can access is just going to keep increasing, and so every organization needs a well thought out strategy for how to optimally ingest, process and consume that data to maximize the value of the data. As such, the role of the data engineer is going to keep growing in importance, even as the technology and approaches to working with large datasets continues to evolve. There are some exciting new technologies that are going mainstream now that enable data engineers to work with object data in a data lake in ways that are similar to working with data in a data warehouse or database. These include AWS Lake Formation Governed Tables, Databricks Delta Lake, Apache Hudi, and others.

Q. Why should readers choose this book over others already on the market? How would you differentiate your book from its competition?

Gareth: There are not a lot of other books currently on the market that focus on data engineering for AWS specifically. So for anyone wanting to get started with building data engineering pipelines on AWS, this is the book for them.

Q. What are the key takeaways you want readers to come away with from the book?

Gareth: This book is not a deep-dive into any one specific technology, or aspect of a data engineers role. In this book we cover the bigger picture of the various different tasks that a data engineer may be involved in, and as such, I want readers to come away with a good broad understanding of the different potential aspects of a data engineers role, as well as related roles.

Q. What advice would you give to readers learning tech? Do you have any top tips?

Gareth:  Get hands-on as much as possible to cement your learning. In this book, every chapter has a hands-on exercise. Also, you can experiment and build at a small-scale in the cloud at a very low cost (or often even at no cost with the AWS Free Tier).When learning a new tech, start with an introduction to a technology (such as by reading the relevant chapter in this book), and then use additional resources to dive-deep (official documentation, blog posts, on-line courses, etc)

Q. Do you have a blog that readers can follow?

Gareth: No, not currently, but I am planning to write more articles on LinkedIn so follow me there!

Q. Can you share any blogs, websites and forums to help readers gain a holistic view of the tech they are learning?

Gareth: There are many resources out there for data engineering, but two I’d highlight are the Data Engineering Podcast (https://www.dataengineeringpodcast.com/about/), and the Reddit Data Engineering subreddit (https://www.reddit.com/r/dataengineering/)

Q. How would you describe your author journey with Packt? Would you recommend Packt to aspiring authors?

Gareth:  The Packt team (including Sean and Arparna, and many others) were great in helping to guide and keep me on track with the book. Writing a book takes a lot of time and hard work, but I found that I mostly enjoyed the process.

Q. What is that one writing tip that you found most crucial and would like to share with aspiring authors?

Gareth: Take each chapter one at a time, and set yourself a deadline for completing the first draft of the chapter. You also need to make sure that every week you have time set aside to work on the book – you can’t just try fit it in between other things.

You can find Gareth’s book on Amazon by following this link