Cracking the Data Engineering Interview: Land your dream job practicing 50 mock questions, resume-building tips, and building a unique portfolio

Get to grips with the fundamental concepts of data engineering, and solve mock interview questions while building a strong resume and a personal brand to attract the right employers

Key Features

• Develop your own brand, projects, and portfolio with expert help to stand out in the interview round
• Get a quick refresher on core data engineering topics, such as Python, SQL, ETL, and data modeling
• Practice with 50 mock questions on SQL, Python, and more to ace the behavioral and technical rounds
• Purchase of the print or Kindle book includes a free PDF eBook

Book Description

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.

What you will learn

• Create maintainable and scalable code for unit testing
• Understand the fundamental concepts of core data engineering tasks
• Prepare with over 100 behavioral and technical interview questions
• Discover data engineer archetypes and how they can help you prepare for the interview
• Apply the essential concepts of Python and SQL in data engineering
• Build your personal brand to noticeably stand out as a candidate

Who this book is for

If you’re an aspiring data engineer looking for guidance on how to land, prepare for, and excel in data engineering interviews, this book is for you. Familiarity with the fundamentals of data engineering, such as data modeling, cloud warehouses, programming (python and SQL), building data pipelines, scheduling your workflows (Airflow), and APIs, is a prerequisite.

Table of Contents

1. The Roles and Responsibilities of a Data Engineer
2. Must-Have Data Engineering Portfolio Projects
3. Building Your Data Engineering Brand on LinkedIn
4. Preparing for Behavioral Interviews
5. Essential Python for Data Engineers
6. Unit Testing
7. Database Fundamentals
8. Essential SQL for Data Engineers
9. Database Design and Optimization
10. Data Processing and ETL
11. Data Pipeline Design for Data Engineers
12. Data Warehouses and Data Lakes
13. Essential Tools You Should Know About
14. Continuous Integration/Continuous Development for Data Engineers
15. Data Security and Privacy
16. Additional Interview Questions

Kedeisha Bryan is a data professional with experience in data analytics, science, and engineering. She has prior experience combining both Six Sigma and analytics to provide data solutions that have impacted policy changes and leadership decisions. She is fluent in tools such as SQL, Python, and Tableau.

She is the founder and leader at the Data in Motion Academy, providing personalized skill development, resources, and training at scale to aspiring data professionals across the globe. Her other works include another Packt book in the works and an SQL course for LinkedIn Learning.

Taamir Ransome is a Data Scientist and Software Engineer. He has experience in building machine learning and artificial intelligence solutions for the US Army. He is also the founder of the Vet Dev Institute, where he currently provides cloud-based data solutions for clients. He holds a master's degree in Analytics from Western Governors University.