12 Essential Data Engineering Interview Questions and Answers
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One of the most substantial economic effects of the COVID-19 pandemic was the acceleration of workplace trends like the transition to remote work. While some businesses needed to shut their doors amid the economic slowdown, others have been growing and interviewing this whole time. Companies like GitHub, Salesforce, Oracle, and Pfizer were among the top for remote job offerings in the past year.
If you’re an aspiring data engineer, don’t let the pandemic hold your career prospects back any longer. Look for remote data engineering positions at companies like these. Chances are, you’ll be invited for an interview (although it may just be nothing but Zoom calls). So, all that being said, how can you prepare for the data engineering interview in 2021?
4 Essential Data Engineering Skills to Practice
First and foremost, aspiring data engineers need to prepare by practicing (or learning) the necessary skills for any data engineering position. These are:
1. General Programming
As you can expect, one of the most crucial skills a data engineer needs to have (and prepare for) is coding. The more command you have over coding, the more likely it is that you will become an efficient Data Engineer or Data Scientist. Be sure to study the basics of data structures and algorithms before your interviews. For instance, an aspiring data engineer should know exactly when a certain data structure or algorithm is best for a given situation. They should also be able to explain why this is the case.
To help prepare, check out the Springboard Intro to Python for Data Science course.
Being a position in the data science field, it should come as no surprise that SQL is another vital skill for data engineering. As a matter of fact, data engineering candidates may find that they need to complete two different technical interviews, one for SQL and another for other coding skills. Many different data science positions require competency with SQL. Data engineers, however, are expected to have some of the most advanced SQL skills, considering their critical role in building reliable and scalable data processing and modeling tools that are deeply consequential for their company.
Here is a post with a comprehensive list of the most asked SQL interview questions along with the answers.
To help prepare, check out the Khan Academy SQL Course.
3. Database Design
Database and system design is another crucial skill for any data engineer. As such, most companies will ask their candidates to design a data warehouse given some real-life parameters or use cases. Be sure to use the whiteboard during these parts of the interview to illustrate your particular way of designing data systems.
To help prepare, check out this Database Structure and Design Tutorial by Lucidchart.
4. Data Architecture and Big Data Frameworks
Most companies will expect their candidates to be competent with specific big data frameworks like Hadoop, Kafka, Spark, or Hive. The best way to prepare is to become comfortable with as many of these frameworks as possible. You can also find a lot of educational value in the official documentation for each framework.
To help prepare, check out the Springboard Data Analysis With Python, SQL, and R learning path.
What’s a Typical Data Engineering Interview Structure?
1. Phone Screenings
Most candidates will need to complete some initial phone screenings before being invited for an in-person interview. For data engineering interviews, candidates will need to complete a screening with an HR rep or hiring manager along with another technical screening.
2. Take-Home Assignments
Some companies may have their candidates initially complete a take-home project to test their technical skills. Before inviting a candidate to an on-site interview, the hiring managers will need a good assessment of their data engineering skills. A take-home coding challenge is the best way to do that in the beginning stages.
3. On-Site Interview
Finally, if a candidate passes the previous interview stages, they will be invited to an on-site interview. Data engineering interviews have the potential to be a strenuous matter, with candidates sitting down with up to 10 people in an 8 hour day. The length and rigor of these interviews may come as a surprise to those not expecting them.
5 Data Engineering Interview Tips
While studying the necessary fundamental skills is the best way to prepare for a data engineering interview, there are other additional ways to give yourself an edge.
- Complete coding challenges with LeetCode or HackerRank: At some point, either during your phone screening or the on-site interview, or both, you will need to complete some programming assignments. The best way to prepare for this is by doing some beforehand using something like LeetCode or HackerRank.
- Practice with the Whiteboard: During the technical interview questions, you will have the opportunity to use the Whiteboard. If candidates are not accustomed to using the Whiteboard in this way, they may not take advantage of it as much as they need to. For this reason, you should practice using the Whiteboard to answer data engineering questions.
- Practice your soft skills: Data engineering is indeed a primarily technical position, but that doesn’t mean your soft skills don’t matter! You’ll definitely be asked some behavioral questions regarding your soft skills, so be sure to practice them as much as anything else.
- Use the STAR method for behavioral questions: When you are inevitably asked those behavioral questions, you can use the STAR Method to answer them sufficiently.
- Review documentation and best practices: Data engineering candidates can also find a foundation for their knowledge in the documentation or best practices of widely used frameworks or tools.
Data Engineer Interview Questions & Answers
Technical Data Engineer Interview Questions
1. What is an example of an unanticipated problem you faced while trying to merge data together from many different places? What was the solution you found?
In this question, the interviewer will inquire about your capacity to handle unexpected problems along with the creativity you use while solving them. Ideally, candidates will come prepared with several experiences they can choose from to answer this question.
2. What ETL tools or frameworks do you have experience with? Are there any you prefer over others?
ETL is a fundamental procedure in SQL. As such, every hiring manager will ask some questions about your knowledge of the ETL process. Your interviewers will be especially interested in your experience with different ETL tools. Therefore, candidates should reflect and think about the ETL tools they have worked with before. When you are asked for your favorite, be sure to answer in a way that also demonstrates your knowledge about the ETL process more generally.
3. Do you have experience with designing data systems using the Hadoop framework or something like it?
Hadoop is a software framework that is often asked about during data engineering interviews. You can know which frameworks your interviewers will ask about beforehand by consulting the job posting. You should expect a question similar to this one during your interview. As such, you should be sure to do your homework and become familiar with the languages and frameworks the job requires. When giving your answer, provide a detailed account of the projects you completed using the framework. Give your interviewer some tangible examples to highlight your experience and competency with the framework.
4. What frameworks or tools are necessary for successful data engineering?
While your interviewers will inevitably ask about your experience with their required frameworks, they will also ask for your personal preferences. These questions also investigate your understanding of the essential requirements for the role while also assessing their technical data skills. Be sure to be as detailed and precise as you can when explaining why you prefer the frameworks and tools you do.
5. What is your experience with cloud computing technologies? What are the costs and benefits associated with using them for data engineering?
All data engineers, nowadays, cannot avoid cloud computing technologies or services. More and more, data is stored entirely on the cloud. There are advantages and disadvantages of this. Data engineering candidates are expected to be knowledgeable in this regard, even if they never had any direct experience with cloud computing. Hiring managers need to confirm that their data engineering candidates are familiar with the different technologies used in the industry.
6. How much experience do you have with NoSQL? Give me an example of a situation where you decided to create a NoSQL database instead of a relational database. Why did you do so?
Any data engineer worth their salt will need to know when to use one type of database over another. There may have been times where you needed to build a NoSQL database rather than a relational database, and your interviewer may be interested in learning why. These questions are investigating your knowledge of databases in general. As such, be sure to demonstrate this knowledge with concrete examples.
7. Do you have any experience with data modeling? If so, what data modeling tools did you use?
Many data engineers have some experience with data modeling, it may well be within the expected responsibilities of data engineers in some organizations. Some interviewers may ask a question like this. If so, be sure to catalog the modeling tools you worked with in the past. Don’t forget to include details on the advantages and disadvantages of each. If you have knowledge or experience with data modeling, this question is your time to shine!
Get To Know Other Data Science Students
Behavioral Data Engineer Interview Questions
1. Tell me about a time you suggested a change to improve the reliability and quality of company data. Were those changes ever made? Why or why not?
Your interviewer will be most interested in the improvements you can bring to the table as a data engineering candidate. They may ask some variation of this question to see how you take the initiative in improving things in your role. If you are asked this question, be sure to point out how your previous experience demonstrates that you are a self-starter. However, if you do not yet have this experience, be sure to prepare some remarks on the improvements you would and could be making if offered the job. Ultimately, be sure to keep your answer focused on the actual methods you employ as a data engineer to improve the quality of data for your organization.
2. What are the non-technical or soft skills that are the most invaluable for data engineers?
Technical data skills, it goes without saying, are the foundation of a data engineering role. This does not mean, however, that data engineering candidates can have these skills and nothing else. Many non-technical skills are vital to successful data engineering. Be sure to be creative when delivering your answer. Try to tell your interviewer something that has not been heard before for this question.
3. What are the fundamental characteristics necessary for a data engineer?
This is, in part, a culture-fit question. The hiring managers will be interested in comparing your conception of a skilled data engineer with that of the company. If there is a significant disparity between the company and the candidate, there may not be a cultural fit. Be sure to explain the skills and capabilities you believe to be vital for any data engineer.
4. What is the most significant professional hurdle you have encountered working as a data engineer?
One of the primary goals of behavioral questions is to investigate how candidates handle conflicts in the workplace. Your interviewer will be less interested in the actual details of what the hurdle was. Instead, they will be interested in how you handled the conflict and how determined you acted in the face of a challenge. It is best to use the STAR method to ace these kinds of behavioral questions.
5. How would you begin the development of a new product working as a data engineer?
These kinds of questions investigate your level of understanding of the product development cycle, especially how data engineering fits into the puzzle. To ace this question, be sure to detail how your data engineering skills could simplify or improve product development at that particular organization. You could use examples from your previous experiences, but you should come prepared with sufficient knowledge of the company’s products. For instance, if you were to answer this question by describing the ways you would improve the product development of that company’s flagship product, your chances of nailing this question are high.
This blog post is written by Anthony Pellegrino, a guest writer for Springboard.
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