11 Top Data Engineer Interview Questions in 2023
Want to hire your next data engineer? Then, you need the right data engineer interview questions. Today, we share our top 11 questions to ask data engineers and identify the right candidate for your team.
Data engineer interviews
Data engineering is a confluence between data science and software engineering. A data engineer needs a variety of skills, including different technologies, languages, and frameworks such as Python, SQL, and Java.
But how do you choose the best data engineers? With the right data engineer interview questions. Here’s what you need to know.
Beginner data engineer interview questions
Let’s start with some junior data engineer interview questions. What are the best questions to ask candidates who don’t have a lot of experience? Here are our top picks.
1. What is data engineering?
Data engineering focuses on data collection and research. More specifically, data engineers help to convert raw data into useful information by designing and building pipelines that transform and transport data into a usable format.
The collection and processing of information happen through a combination of desktop software, mobile applications, cloud-based servers, and physical infrastructure. Data engineers collaborate with data scientists, who analyze and use the data that is collected.
2. What skills do data engineers need?
A data engineer needs the following skills:
Programming; the most common languages are Python, Scala or Java.
Software engineering, including DevOps, Agile, architecture design, and service-oriented architecture.
Open frameworks, including Apache Spark, Hadoop, Hive, MapReduce, Kafka, and others.
Pandas, a Python library for cleaning and manipulating data.
Cloud platforms, Amazon Web Services is the most common cloud skill set, but Google Cloud Data and Microsoft Azure are other options.
An understanding of analytics, such as statistical analysis skills and different mathematical principles.
3. Are you database or pipeline-centric?
This question helps you assess if a candidate has a focus area and if it matches your needs. If they are a generalist, they might have more experience working for smaller companies and if you run a bigger organization, you will need to know how their skills fit into your team.
4. What’s your process for developing a new product?
Data engineers need good project management skills. Ask them to share how they would start the process of building a new product to see what their approach is. Look for answers that mention how they would streamline the development process.
For instance, they might request an outline of the project to understand the complete scope and requirements and the questions they’d ask at this first project stage.
Advanced data engineer interview questions
How do you choose the best senior data engineers? Here are interview questions to ask candidates who have more experience.
5. Have you worked with a cloud computing environment? What are the pros and cons?
Most advanced data engineers have cloud computing experience and even if not, they need to be able to demonstrate an understanding of its pros and cons.
Cloud computing is cost-effective and reliable because most providers guarantee a high level of service availability. The con is that a cloud computing environment can compromise data security and privacy and limit control because data is being kept outside the company.
6. Have you ever introduced a new data analytics application? What challenges did you face and how did you overcome them?
New data applications are pricey and incorporating them into an organization can be a big and tedious project where you need to train employees and integrate the tool into your workflow, so you’d need to be sure that the tool is one your organization truly needs. Candidates should outline their overall approach, as well as examples of unforeseen issues that could arise (such as licensing or training issues).
7. What are the different components of a Hadoop application?
The different components of a Hadoop application are:
Hadoop Common: A common set of utilities and libraries that are utilized by Hadoop.
Hadoop MapReduce: Based on the algorithm to provide large-scale data processing.
HDFS: Hadoop application that relates to the file system where Hadoop data is stored. It’s a distributed file system with high bandwidth.
Hadoop YARN: Used for resource management within the Hadoop cluster.
8. What is your experience with NoSQL databases? When is it better to build a NoSQL database than a relational database?
This question gives you some insight into how well data engineers understand different databases. Databases have their pros and cons and data engineers should be able to explain them. In terms of NoSQL databases, they offer a way to store and retrieve data that is modeled in means other than the tabular relations used in relational databases. For instance, when an organization needs scale, NoSQL databases can be a good option.
9. Have you trained others to use software, applications, processes, or architecture? What’s the most challenging part?
Data engineers need to know how to train their co-workers on new processes and systems or already existing architectures and pipelines. As insufficient training can quickly become a bottleneck in an organization, you want to make sure that your candidate has some training experience. And by asking for the challenging parts of training co-workers, you get some insight into their thinking and approach to training.
10. How do you deploy a big data solution?
To deploy a big data solution, you need to:
Integrate data using data sources like SAP, RDBMS, MySQL, and Salesforce
Store extracted data in NoSQL database or HDFS.
Deploy a big data solution using Pig, Spark, or MapReduce or other processing frameworks.
11. How do you achieve security in Hadoop?
First, secure the authentication channel of the client to the server and provide it time-stamped to the client.
Then, the client uses the time stamp to request TGS for a service ticket.
Last, the client uses the service ticket for self-authentication to a specific server.
Build a world-class data engineering team
There you have it! Now you know what data engineer interview questions to ask.
Once you’ve interviewed your candidates, you also need to assess their skills.
CodeSubmit offers industry-leading technical skill assessments.