AlgoDaily - Data Engineering Interview Questions Cheat Sheet

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ADDITIONAL INTERVIEW QUESTIONS

When data engineering roles are in question, the dominant part of the coding assessment relies on the data side, not on the algorithm side. Be ready to solve practical problems! Below are a few more examples of questions you may encounter very often in a data engineering interview.

QUESTION 6

The task is to construct a SQL query that will show the unique number of occurrences of one class within a single column.

Small help: You can get required results by using the next SQL functions: SELECT, COUNT, FROM, GROUP BY

QUESTION 7

Name three Python libraries that can be used for data processing tasks.

Answer: Numpy, Pandas, TensorFlow

QUESTION 8

Your assignment is to visually present outliers from a data set. Name one library and its function, which is an adequate solution for this kind of visualization.

Possible answers: Box plot, Scatter plot

QUESTION 9

The volume of data is rapidly increasing. What is your plan to add more capacity to the existing architecture?

Possible answers: You can request more database instances in the cloud on Google Cloud Platform, for example. Or to suggest removing old data sets and better data compression. Try to research on your own more solutions for this problem.

QUESTION 10

Name the main components of Hadoop. And, of course, what is Hadoop?

Answer: Shortly explained, Hadoop is the tool for processing Big data. Two main components of Hadoop are HDFS and MapReduce.

Suppose you know the answers to the previous questions on your own. In that case, you are well on your way to successfully passing one interview for Data Engineer. If you have problems solving these questions, try to investigate occurred issues and find solutions yourself. In any case, let this tutorial be the basis and starting point for mastering new data engineering knowledge. Be curious and don't just dwell on case studies and problems in the existing literature. Find yourself a real problem based on existing databases, approach it from a data engineer's point of view, and go through the entire development path from data collection to analysis. It will undoubtedly be fun, and more importantly, you will gain valuable practical experience in working with data!