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Cracking the Data Engineering Interview

Cracking the Data Engineering Interview

By : Kedeisha Bryan, Taamir Ransome
4.6 (5)
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Cracking the Data Engineering Interview

Cracking the Data Engineering Interview

4.6 (5)
By: Kedeisha Bryan, Taamir Ransome

Overview of this book

Preparing for a data engineering interview can often get overwhelming due to the abundance of tools and technologies, leaving you struggling to prioritize which ones to focus on. This hands-on guide provides you with the essential foundational and advanced knowledge needed to simplify your learning journey. The book begins by helping you gain a clear understanding of the nature of data engineering and how it differs from organization to organization. As you progress through the chapters, you’ll receive expert advice, practical tips, and real-world insights on everything from creating a resume and cover letter to networking and negotiating your salary. The chapters also offer refresher training on data engineering essentials, including data modeling, database architecture, ETL processes, data warehousing, cloud computing, big data, and machine learning. As you advance, you’ll gain a holistic view by exploring continuous integration/continuous development (CI/CD), data security, and privacy. Finally, the book will help you practice case studies, mock interviews, as well as behavioral questions. By the end of this book, you will have a clear understanding of what is required to succeed in an interview for a data engineering role.
Table of Contents (23 chapters)
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1
Part 1: Landing Your First Data Engineering Job
6
Part 2: Essentials for Data Engineers Part I
11
Part 3: Essentials for Data Engineers Part II
16
Part 4: Essentials for Data Engineers Part III
20
Chapter 16: Additional Interview Questions

Summary

Preparing for behavioral interviews is critical to any job search, especially for data engineering positions. Candidates can better prepare for success by understanding the types of behavioral questions commonly asked in data engineering interviews and the skills that are measured during these interviews.

This chapter discussed six main types of behavioral questions, including those that assess cultural fit and the STARR method for effectively answering behavioral questions. We also reviewed the top 10 most frequently asked questions in a data engineering interview and provided detailed explanations of how to answer them.

By employing these strategies and best practices, candidates can increase their chances of success in a data engineering interview and effectively demonstrate their skills and qualifications. As the demand for data engineering roles grows, being well prepared for these interviews is more crucial than ever. We hope this chapter has provided candidates...

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