Cracking the Data Engineering Interview (eBook)
196 Seiten
Packt Publishing (Verlag)
978-1-83763-107-0 (ISBN)
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.
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 employersKey FeaturesDevelop your own brand, projects, and portfolio with expert help to stand out in the interview roundGet a quick refresher on core data engineering topics, such as Python, SQL, ETL, and data modelingPractice with 50 mock questions on SQL, Python, and more to ace the behavioral and technical roundsPurchase of the print or Kindle book includes a free PDF eBookBook DescriptionPreparing 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 learnCreate maintainable and scalable code for unit testingUnderstand the fundamental concepts of core data engineering tasksPrepare with over 100 behavioral and technical interview questionsDiscover data engineer archetypes and how they can help you prepare for the interviewApply the essential concepts of Python and SQL in data engineeringBuild your personal brand to noticeably stand out as a candidateWho this book is forIf 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.
Erscheint lt. Verlag | 7.11.2023 |
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Sprache | englisch |
Themenwelt | Informatik ► Datenbanken ► Data Warehouse / Data Mining |
Informatik ► Software Entwicklung ► User Interfaces (HCI) | |
Mathematik / Informatik ► Informatik ► Theorie / Studium | |
Mathematik / Informatik ► Informatik ► Web / Internet | |
ISBN-10 | 1-83763-107-7 / 1837631077 |
ISBN-13 | 978-1-83763-107-0 / 9781837631070 |
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