If you are an aspiring Data Engineer looking for a guide on how to land, prepare, and excel in data engineering interviews, then this book is for you. You should already understand and should have been exposed to fundamentals of Data Engineering such as data modeling, cloud warehouses, programming (python & SQL), building data pipelines, scheduling your workflows (Airflow), and APIs.
Table Of Contents
What this book covers
Chapter 1, The Roles and Responsibilities of a Data Engineer, explores the complex array of responsibilities that comprise the core of a data engineer’s role. This chapter unifies the daily responsibilities, long- term projects, and collaborative obligations associated with the title, thereby offering a comprehensive perspective of the profession.
Chapter 2, Must-Have Data Engineering Portfolio Projects, this chapter helps you dive deep into a selection of key projects that can showcase your prowess in data engineering, offering potential employers tangible proof of your capabilities.
Chapter 3, Building Your Data Engineering Brand on LinkedIn, this chapter shows you how to make the most of LinkedIn to show off your accomplishments, skills, and goals in the field of data engineering.
Chapter 4, Preparing for Behavioral Interviews, Along with technical skills, the most important thing is that you can fit in with your team and the company’s culture. There are tips in this chapter on how to do well in behavioral interviews so that you can talk about your strengths and values clearly.
Chapter 5, Essential Python for Data Engineers, Python is still an important tool for data engineers. This chapter will help you learn about the Python ideas, libraries, and patterns that every data engineer needs to know.
Chapter 6, Unit Testing, In data engineering, quality assurance is a must. This chapter will teach you the basics of unit testing to make sure that your data processing scripts and pipelines are reliable and strong.
Chapter 7, Database Fundamentals, At the heart of data engineering lies the database. In this chapter you will acquaint yourself with the foundational concepts, types, and operations of databases, establishing a solid base for advanced topics.
Chapter 8, Essential SQL for Data Engineers, SQL is the standard language for working with data. This chapter will help you learn the ins and outs of SQL queries, optimizations, and best practices so that getting and changing data is easy.
Chapter 9, Database Design and Optimization, It’s both an art and a science to make databases work well. This chapter will teach you about advanced design principles and optimization methods to make sure your databases are quick, scalable, and reliable.
Chapter 10, Data Processing and ETL, Turn raw data into insights that can be used. In this chapter we will learn about the tools, techniques, and best practices of data processing in this chapter, which is about the Extract, Transform, Load (ETL) process.
Chapter 11, Data Pipeline Design for Data Engineers, A data-driven organization needs to be able to easily move data from one place to another. In this chapter you will learn about the architecture, design, and upkeep of data pipelines to make sure that data moves quickly and reliably.
Chapter 12, Data Warehouses and Data Lakes, Explore the huge world of ways to store data. This chapter teaches you the differences between data warehouses and data lakes, as well as their uses and architectures, to be ready for the challenges of modern data.
Chapter 13, Essential Tools You Should Know About, It’s important to have the right tool. In this chapter you will learn how to use the most important tools in the data engineering ecosystem, from importing data to managing it and keeping an eye on it.
Chapter 14, Continuous Integration/Continuous Development for Data Engineers, Being flexible is important in a world where data is always changing. In data engineering and in this chapter, you will learn how to use CI/CD to make sure that data pipelines and processes are always up-to-date and running at their best.
Chapter 15, Data Security and Privacy, It’s important to be responsible when you have a lot of data. This chapter will teach you about the important issues of data security and privacy, and get to know the best ways to protect your data assets and the tools you can use to do so.
Chapter 16, Additional Interview Questions, Getting ready is half the battle won. This chapter comprises of carefully chosen set of interview questions that cover a wide range of topics, from technical to situational. This way, you’ll be ready for any surprise that comes your way.
To get the most out of this book
You will need to have a basic understanding of Microsoft Azure.
| Software/hardware covered in the book | Operating system requirements |
|---|---|
| Microsoft Azure | Windows, macOS, or Linux |
| Amazon Web Services | Windows, macOS, or Linux |
| Python | Windows, macOS, or Linux |
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See also
- Software Exorcism: A Handbook for Debugging and Optimizing Legacy Code by Bill Blunden (2003)
- Hormones and the Endocrine System: Textbook of Endocrinology by Bernhard Kleine (2016)
- Genetics: A Conceptual Approach 6e by Benjamin A. Pierce (2017)
- A Functional Approach to Java by Ben Weidig (2022)
- Calculus of variations and optimal control by Amol Sasan (2005)