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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

Essential Python for Data Engineers

Finding your way through the data engineering interview process can be challenging, particularly when it comes to showcasing your technical expertise. Python is frequently the preferred language for data engineering tasks because of its ease of use, readability, and rich library support. A solid understanding of Python is essential for anyone working with data Extraction, Transformation, and Loading (ETL) procedures or developing intricate data pipelines.

This chapter aims to give you the Python knowledge you need to succeed in a data engineering position. We’ll begin by discussing the fundamental Python skills that each data engineer should be familiar with. We’ll then get into more complicated subjects that will make you stand out from other candidates. We’ll finish the chapter with some technical interview questions that assess your knowledge of Python in the context of data engineering.

In this chapter, we will cover...

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