10 Tips to prepare for data engineer interview questions

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10 Hacks to Prepare for Data Engineering Interviews

Data engineers are a crucial part of the tech team and are responsible for data cleaning, preparation, maintaining data pipeline, and more. Despite the pandemic, the demand for data engineers is quite high and many companies are actively recruiting them. We have earlier covered tips for you to prepare a resume for data engineering interviews and data engineering skills that you should master to excel in your career. In this blog, we will cover a few hacks and tips to prepare for these interviews and have a successful data engineer career path.

  1. Practice coding: One of the crucial skills for data engineers is to have coding skills. Python, R, Scala are some of the programming languages you should be familiar with. Most of the data engineer interview questions are around languages, designing algorithms, and working with data structures. Real-time practicing with coding is the only way forward to acquire the skills. There are several platforms such as Codewars, Geektastic, freeCodeCamp, Coderbyte, Datacamp, and more that allow building projects and strengthen your coding skills for the next data engineering interview.
  2. Practice SQL: SQL is a crucial skill for data engineering job roles and SQL interview questions are a major focus in data engineering interviews. Candidates are expected to have advanced skills in SQL to be able to build reliable and scalable data processing models. There are platforms such as Hackerrank that allow you to solve problems based on SQL skills. Another resource SQLZOO can help you with learning basics and write more efficient SQL queries.
  3. Build real-time data architecture: Platforms such as Leetcode allow working on specific concepts of data engineering such as building data structures or architectures. It allows you to practice easy to medium-level problems to get a good understanding of the concepts. It also includes month-long challenges that equip you with a problem-solving approach.
  4. Refer to the official documentation: To prepare for big data technologies and concepts such as Hadoop, Kafka, Spark, Hive, Cassandra, or more, one of the best ways to learn more about them is through official documentation. It gives detailed insights into their workings, best practices to follow, and keep you abreast with the latest developments in these tools.
  5. Focus on problem-solving and thought process: While working on a data engineering project, apart from implementing the right tools and technologies, it is important to focus on the way you are approaching the problem. Most interviewers would like to know your thought process and the way you approach the problem. Break the projects that you have done so far into smaller parts and practice explaining each of the processes and technologies in detail.
  6. Practice with whiteboard or paper: While it may look like a quite generic hack, working up your problems and chalking the solution approach on whiteboard or paper can help you with all the practice required to appear for your next interview. Most data engineering interviewers expect candidates to explain a problem on whiteboards. It will provide practice to appear for these interviews and answer the queries more efficiently.
  7. Solve puzzles. Lot’s of it: Puzzles form a crucial part of Data engineering and data science interview that helps interviewers quickly understand your analytical skills and thought process. It is therefore a good idea to solve as many puzzles and quizzes as possible to get more logical, creative, and quick with numbers.
  8. Real-time practicing with experts: With platforms such as Pramp, you can practice for data engineering interviews in real-time with subject matter experts. It helps prepare for the interviews by overcoming your fear and anxieties and prepare for technical questions that are expected in actual interviews. It prepares for a high-pressure environment while letting you work on soft skills.
  9. Participate in hackathons, competitions, and conferences: Participating in hackathons and competitions helps you with strengthening your skills and understanding of the subject. There are many hackathon platforms such as Kaggle, Machine Hack, HackerEarth, and more that let you not only practice but also compete with other professionals in the industry. There are other competitions such as Google Code Jam, CodeChef, and others to compete.
  10. Focus on the resume: It goes without saying that a resume is your first introduction to you and it needs to stand out. It should focus on all the big data and data engineering skills that you have acquired over the years. Also, be sure to be able to explain all the tools and technologies that you have listed on the resume to the interviewer. Read more about how to prepare a resume for a data engineering interview here.

About the Author

Srishti is Content Marketing Manager at Sigmoid with a background in tech journalism. She has extensively covered Data Science and AI space in the past and is passionate about technologies defining them.