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

Product type Paperback

Published in Nov 2023

Publisher Packt

ISBN-13 9781837630776

Length 196 pages

Edition 1st Edition

Languages

Python

Tools

Core Data

Concepts

Data Engineering

Authors (2):

Kedeisha Bryan

Taamir Ransome

View More author details

Table of Contents (23) Chapters

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

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Data Security and Privacy

Scale, efficiency, design, and (possibly most importantly) security and privacy all play important roles in navigating the world of data engineering. These components govern how safely and responsibly data is handled, not just as additional layers on top of the existing data landscape. Knowing how to secure and privatize this information is essential, whether you’re working with confidential customer information, top-secret corporate documents, or even just operational data.

Security is a primary concern that must be integrated starting with the design phase and continuing through deployment and maintenance in the world of data engineering. Just as data privacy used to be a nice-to-have, it is now a must-have, thanks to regulations such as the General Data Protection Regulation (GDPR) and the California Consumer Privacy Act (CCPA).

We want you to leave this chapter with a firm grasp of the fundamental ideas and procedures underlying data security...