Grasp foundational concepts in data engineering and tackle pilot questions while building a powerful resume and a personal brand to attract the right employers.
1. Main features:
✓ Develop your own brand, projects and portfolio with expert help to stand out in the interview round.
✓ Quick updates on core data engineering topics, such as Python, SQL, ETL, and data modeling.
✓ Practice with 50 simulated questions on SQL, Python, and more. to pass the behavioral and technical rounds.
2. Book description:
Preparing for a data engineering interview can often become overwhelming due to the plethora of tools and technologies available, making it difficult to prioritize which issues to focus on. This practical guide gives you the foundation and advanced knowledge you need to simplify your learning journey.
The book begins by giving you a clear understanding of the nature of data engineering and how it differs from organization to organization. As you read through the chapters, you’ll get expert advice, practical tips, and practical insights on everything from creating resumes and cover letters to networking and negotiating your salary. Chapters also provide refresher training on the essentials of data engineering, including data modeling, database architecture, ETL processes, data warehousing, cloud computing, big data, and machine learning. As you advance, you’ll gain a comprehensive perspective 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 it takes to succeed in an interview for a data engineering position.
3. What you will learn:
✓ Create maintainable and scalable code for unit testing.
✓ Understand the foundational concepts of core data engineering tasks.
✓ Prepare with over 100 behavioral and technical interview questions.
✓ Explore data engineer archetypes and how they can help you prepare for your interview.
✓ Apply essential concepts of Python and SQL in data engineering.
✓ Build your personal brand to stand out more as a candidate.
4. Who is this book for:
If you’re an aspiring data engineer looking for guidance on how to land, prepare, and excel at data engineering interviews, this book is for you. Familiarity with the foundations 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 .
5. Table of contents:
✓ Chapter 01: Roles and responsibilities of a Data Engineer.
✓ Chapter 02: Must-have Data Engineering Portfolio Projects.
✓ Chapter 03: Building your Data Engineering Brand on LinkedIn.
✓ Chapter 04: Prepare for Behavioral Interview.
✓ Chapter 05: Python is essential for Data Engineers.
✓ Chapter 06: Unit Testing.
✓ Chapter 07: Database Fundamentals.
✓ Chapter 08: Necessary SQL for Data Engineers.
✓ Chapter 09: Database Design and Optimization.
✓ Chapter 10: Data Processing and ETL.
✓ Chapter 11: Data Pipeline Design for Data Engineers.
✓ Chapter 12: Data Warehouses and Data Lakes.
✓ Chapter 13: Essential tools you should know.
✓ Chapter 14: Continuous Integration/Continuous Development for Data Engineer.
✓ Chapter 15: Data Security and Privacy.
✓ Chapter 16: Additional interview questions.
Link download : https://drive.google.com/drive/folders/1_q8g9_TBy-lRWd81gl9-BEhMaW4Wj2I_
Password open file : https://drive.google.com/drive/folders/1lna5LnxuP3DTN6hx-cMYuYdzNboyIhIB
