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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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Toc

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

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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