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Cracking the Data Engineering Interview

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

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Product type Paperback
Published in Nov 2023
Publisher Packt
ISBN-13 9781837630776
Length 196 pages
Edition 1st Edition
Languages
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Authors (2):
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Kedeisha Bryan Kedeisha Bryan
Author Profile Icon Kedeisha Bryan
Kedeisha Bryan
Taamir Ransome Taamir Ransome
Author Profile Icon Taamir Ransome
Taamir Ransome
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Table of Contents (23) Chapters Close

Preface 1. Part 1: Landing Your First Data Engineering Job
2. Chapter 1: The Roles and Responsibilities of a Data Engineer FREE CHAPTER 3. Chapter 2: Must-Have Data Engineering Portfolio Projects 4. Chapter 3: Building Your Data Engineering Brand on LinkedIn 5. Chapter 4: Preparing for Behavioral Interviews 6. Part 2: Essentials for Data Engineers Part I
7. Chapter 5: Essential Python for Data Engineers 8. Chapter 6: Unit Testing 9. Chapter 7: Database Fundamentals 10. Chapter 8: Essential SQL for Data Engineers 11. Part 3: Essentials for Data Engineers Part II
12. Chapter 9: Database Design and Optimization 13. Chapter 10: Data Processing and ETL 14. Chapter 11: Data Pipeline Design for Data Engineers 15. Chapter 12: Data Warehouses and Data Lakes 16. Part 4: Essentials for Data Engineers Part III
17. Chapter 13: Essential Tools You Should Know 18. Chapter 14: Continuous Integration/Continuous Development (CI/CD) for Data Engineers 19. Chapter 15: Data Security and Privacy 20. Chapter 16: Additional Interview Questions
21. Index 22. Other Books You May Enjoy

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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