Book Image

Cracking the Data Engineering Interview

By : Kedeisha Bryan, Taamir Ransome
1 (1)
Book Image

Cracking the Data Engineering Interview

1 (1)
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)
Part 1: Landing Your First Data Engineering Job
Part 2: Essentials for Data Engineers Part I
Part 3: Essentials for Data Engineers Part II
Part 4: Essentials for Data Engineers Part III
Chapter 16: Additional Interview Questions

Part 1: Landing Your First Data Engineering Job

In this part, we will focus on the different types of data engineers and how to best present yourself in your job hunt.

This part has the following chapters:

  • Chapter 1, The Roles and Responsibilities of a Data Engineer
  • Chapter 2, Must-Have Data Engineering Portfolio Projects
  • Chapter 3, Building Your Data Engineering Brand on LinkedIn
  • Chapter 4, Preparing for Behavioral Interviews