Cracking the Data Engineering Interview
eBook Details:
- Paperback: 196 pages
- Publisher: WOW! eBook (November 7, 2023)
- Language: English
- ISBN-10: 1837630771
- ISBN-13: 978-1837630776
eBook Description:
Cracking the Data Engineering Interview: 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
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.
- 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
By the end of this Cracking the Data Engineering Interview book, you will have a clear understanding of what is required to succeed in an interview for a data engineering role.