Mastering Data Engineering: Common Data Engineer Interview Questions You Should Know

7 min read

How can I get ready for a Data Engineer interview? Our Data Engineer Interview Questions blog contains frequently asked questions you may be asked during interviews with several companies.

Whether you’re a beginner to big data looking for a Data Engineering employment or an experienced Data Engineer looking for new options, preparing for an upcoming interview can be frightening. Given the market’s competitiveness, you must be well-prepared for your interview. Moreover, Interviewing for any position can be nerve-wracking. Data engineer positions in the technology industry can be highly competitive. Numerous individuals are drawn to these professions because they are in high demand, pay well, and have positive long-term job growth.

As you prepare for a potential interview, be confident in your data engineering accomplishments. Due to the high level of competition, some job seekers report applying for hundreds of big data positions before being called in for an interview, despite having the necessary qualifications and skills, so don’t be disappointed if it takes longer than planned. Once you’ve done that, you’ll need to clearly explain why and how you used specific data methodologies and algorithms in a previous project to obtain the job.

The following are some of the most common data engineer interview questions and answers, the reasons why these questions are typically posed, and the types of answers that interviewers usually seek.

Data Engineer Interview Questions

General Data Engineer Interview Questions

Interviewers are curious about who you are and why you want to become a data engineer. In data engineering, the focus is primarily on technical aspects, making it less likely for interviewers to ask behavioral questions, but these higher-level inquiries may appear early in your interview.

1.  Tell Me About Yourself

This question comes up so frequently in job interviews that it can appear vague and open-ended, but it focuses on your relationship with data engineering. Focus your response on your path toward becoming a data engineer. What drew you to this profession or industry? How did you acquire your technical expertise?

The interviewer may also inquire why the candidate decided to pursue a career in data engineering.

Describe the steps you took to become a data engineer.

Also Read: How To Become A Blockchain Engineer in 2023 – Ultimate Guide

2.  What is Data Engineering?

This is one of the more elementary data engineer interview questions, but it could come up regardless of your experience level. Your interviewer wants to know your precise definition of data engineering, demonstrating that you understand the nature of the work. What is it, then? It is transforming, cleansing, profiling, and aggregating vast data sets. You can also elaborate on the day-to-day responsibilities of a data engineer, such as constructing and extracting ad-hoc data queries, owning an organization’s data stewardship, etc.

3.  What is the Role of a Data Engineer Within a Team or Organization?

Recruiters want to know if you are familiar with the responsibilities of a data engineer. How do they work?” What is their function within the team? You should describe the typical duties of a data engineer and their team members. If you have experience as a data scientist or analyst, tell how you collaborated with data engineers.

4.  When Did You Encounter Difficulty Coping with Unstructured Data and How Did You Overcome it?

Data engineers are primarily responsible for developing the systems that acquire, manage, and transform raw data into information that data scientists and business analysts can interpret. This inquiry concerns any obstacles you may have encountered when solving a problem and how you overcame them.

This is your opportunity to demonstrate how you make data more accessible via coding and algorithms. Instead of explaining the technicalities at this point, try to incorporate the specific responsibilities listed in the job description into your response.

Data Engineer Process Questions

Data Engineer Process Questions

Most Data Engineer Interview Questions will focus on the applicant’s previous projects. Even if you’ve never held a data engineering position, you can talk about the projects you’ve worked on in school or posted on GitHub, a platform for managing and hosting computer code that encourages developer collaboration.

5.  Walk Me Through a Project You Completed From Beginning to End

During the interview, the interviewer will ask you to explain your thought process and approach to completing a project. Hiring managers want to know how the unstructured data was transformed into a finished product. You must practice articulating your rationale for understandably selecting particular algorithms to demonstrate your expertise. You will then be asked follow-up queries regarding this project.

6.  Which Algorithm(s) Did You Employ For This Project?

They want to know your rationale for selecting one algorithm over another. Focusing on a project you worked on and relating any follow-up inquiries to that project may be the most straightforward approach. Moreover, if you have a project and algorithm example relevant to the company’s work, use it to convince the interviewer. Describe the models you utilized, followed by the analysis, results, and impact.

7.  Which Tools Did You Utilize For This Project?

Data architects must manage vast amounts of data and use the appropriate tools and technologies to collect and organize it. If you have experience with various tools such as Hadoop, MongoDB, and Kafka, specify which one you used for this assignment.

You can describe the ETL (extract, transform, and load) systems, such as Stitch, Alooma, Xplenty, and Talend, that you used to transfer data from databases into a data warehouse. Some tools perform better for the back end, so if you can demonstrate strong decision-making skills, you will stand out as a confident candidate.

Technical Data Engineer Interview Questions

Technical Data Engineer Interview Questions

Some interviewers may follow up with more technical Data Engineer Interview Questions, for which you may wish to improve your knowledge beforehand. Please familiarise yourself with the concepts outlined in the job description and practice speaking through them.

8.  What is Data Modeling?

Data modeling is the initial stage in database design and data analysis. You will need to clarify that you can demonstrate the relationship between structures using the conceptual, logical, and physical models in that order. This is one of the most Technical Data Engineer Interview Questions.

9.  What Are the Design Schemas of Data Modeling?

Schemas play a fundamental role in data engineering; therefore, when explaining the concepts in typical language, strive for accuracy. Two schemas exist: the star schema and the snowflake schema.

Moreover, the star schema represents the most basic form of a data warehouse schema. It consists of a fact table with multiple dimension tables associated with it, resembling a star. A snowflake schema is an extension of a star schema that adds dimension tables that separate the data into spokes as if it were a snowflake.

10.  Explain The Difference Between Structured Data And Unstructured Data

Data engineers must transform unstructured data into structured data for data analysis using various transformation techniques. First, clarify the distinction between the two.

Structured data consists of well-defined data types with patterns (using algorithms and coding) that make them readily searchable. In contrast, unstructured data is a collection of files in various formats, including videos, photos, texts, and audio.

Moreover, Engineers collect, manage, and store unstructured data in database management systems (DBMS) to transform it into searchable structured data. ELT is the tool to convert and integrate unstructured data into a cloud-based data warehouse. Unstructured data may be entered manually or via batch processing with coding.

Also read: Software Developer Vs Software Engineer | A Comprehensive Comparison

11.  Tell Me About Some of Hadoop’s Most Important Features

Hadoop is an open-source software framework that provides massive storage and processing capacity for storing data and running applications. Your interviewer is testing your knowledge of its significance in data engineering, so you must explain that its compatibility with multiple hardware types makes it easy to access.

Hadoop enables rapid data processing by storing it in a cluster independent of its other operations. It allows the creation of three copies of each block using distinct nodes (collections of computers networked together to process multiple data sets simultaneously). This is one of the most technical interview questions for data engineers.

12.  What Are Big Data’s Four Vs?

Volume, velocity, variety, and veracity are the four Vs. Most likely, the interviewer will ask you what they are and why they are significant. Big data involves collecting, storing, and utilizing massive amounts of data for business purposes. The four Vs must produce the fifth V value.

Volume: It involves processing data sets of significant magnitude (terabytes or petabytes), such as handling daily credit card transactions throughout Latin America.

Velocity: refers to the rate at which data is produced. The velocity of Instagram posts is rapid.

Variety: refers to the numerous structured and unstructured data sources and file types.

Veracity: Refers to the integrity of the data that is being analyzed. Data engineers must comprehend various tools, algorithms, and analytics to generate meaningful data.

Facebook Data Engineer Interview Questions

13.  Why Are Clusters Employed in Kafka And What Are The Benefits?

Multiple brokers distribute data across multiple instances, constituting the Kafka cluster. It can expand without any interruptions. Clusters of Apache Kafka are utilized to prevent delays. If the primary cluster fails, we will use additional Kafka clusters to continue providing the same services

The components of the Kafka cluster architecture are Topics, Broker, ZooKeeper, Producers, and Consumers. It manages data streams for big data and enables the development of data-driven applications.

14.  Which Issues Does Apache Airflow Address?

Apache Airflow lets you manage and plan pipelines for the analytical workflow, the management of a data warehouse, and the transformation and modeling of data all from one place.

In one central location, you can track execution logs, and you can employ callbacks to send failure reports to Slack and Discord.  Lastly, it is free and easy to use, has a helpful user design, and robust integrations.



This collection of interview questions and answers for data engineers covers various data engineering and big data-related technologies. Prepare for Hadoop-related queries and technical questions requiring you to recall past experiences.

Reviewing data engineering questions is a great starting point on the path to a career in data engineering, but there is more to do.

I hope that the information presented here proves to be useful to you. You can share your thoughts about this article in the comments section.

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