Degreed Data Engineer Interview Questions + Guide in 2025

Degreed is a leading platform that empowers individuals and organizations to discover, track, and certify their skills and learning journeys.

As a Data Engineer at Degreed, you will play a pivotal role in designing, building, and maintaining data pipelines and architectures that enable effective data analysis and reporting. Key responsibilities include developing robust ETL processes, ensuring data quality and integrity, and collaborating with data scientists and analysts to understand their data needs. A strong understanding of microservices, data warehousing, and cloud-based technologies is essential, along with proficiency in programming languages such as Python and C#.

To excel in this role, you should be detail-oriented and possess excellent problem-solving skills, as well as the ability to communicate complex technical concepts to non-technical stakeholders. Familiarity with machine learning and data modeling will also set you apart as a candidate who can contribute to Degreed’s mission of enhancing skill development and learning insights.

This guide will help you prepare for your interview by providing insights into the role's expectations and the types of questions you may encounter, allowing you to present yourself as a strong candidate who aligns with Degreed’s values and objectives.

The interview process for a Data Engineer role at Degreed is structured to assess both technical skills and cultural fit within the organization. The process typically unfolds as follows:

1. Initial Phone Interview

The first step in the interview process is a phone interview with a recruiter or HR representative. This conversation usually lasts around 30 minutes and serves as an introduction to the role and the company. During this call, candidates are expected to discuss their background, relevant experiences, and motivations for applying to Degreed. The recruiter will also gauge the candidate's alignment with the company culture and values.

2. Technical Screen

Following the initial phone interview, candidates may undergo a technical screening, which is often conducted via video conferencing. This session typically involves discussions around the candidate's technical expertise, particularly in areas such as data warehousing, coding, and microservices. Candidates should be prepared to answer questions that assess their problem-solving abilities and familiarity with relevant technologies.

3. Take-Home Challenge

A unique aspect of the Degreed interview process is the take-home challenge. Candidates are given a project that requires them to demonstrate their technical skills and thought process. This challenge is designed to be open-ended, allowing candidates to identify a problem, formulate a solution, and present their findings. The emphasis is on clarity of communication, code readability, and the ability to document the problem-solving steps effectively.

4. Team Interviews

After the take-home challenge, candidates typically participate in a series of individual interviews with team members, including the hiring manager and other developers. These interviews delve deeper into technical competencies and may include behavioral questions to assess how candidates work within a team and handle various work scenarios. Candidates should be ready to discuss past projects in detail, including challenges faced and how they collaborated with stakeholders.

5. Final Interview

The final stage of the interview process may involve a wrap-up interview with senior leadership or the hiring manager. This conversation often focuses on the candidate's overall fit within the company and their long-term career aspirations. It’s an opportunity for candidates to ask questions about the company culture, team dynamics, and future projects.

As you prepare for your interview, it’s essential to be ready for the specific questions that may arise during each stage of the process.

Here are some tips to help you excel in your interview for the Data Engineer role at Degreed.

Understand the Company’s Values and Culture

Before your interview, take the time to familiarize yourself with Degreed's mission and values. Understanding their commitment to lifelong learning and how they empower individuals to develop their skills will help you align your responses with their core principles. Be prepared to discuss how your personal values resonate with the company’s culture, as this can set you apart from other candidates.

Prepare for Behavioral Questions

Given the feedback from previous candidates, it’s crucial to prepare for behavioral questions that explore your past experiences. Be ready to discuss specific projects where you played a leading role, focusing on the challenges you faced, how you collaborated with stakeholders, and the impact of your solutions. Use the STAR (Situation, Task, Action, Result) method to structure your responses clearly and effectively.

Showcase Your Technical Expertise

As a Data Engineer, you will need to demonstrate your technical skills confidently. Be prepared to discuss your experience with data warehousing, ETL processes, and relevant programming languages such as Python or C#. Additionally, you may encounter a take-home challenge that assesses your problem-solving abilities. Approach this task methodically, documenting your thought process and ensuring your code is clean and well-structured. Quality presentation of your findings is just as important as the technical solution itself.

Be Ready for Open-Ended Challenges

Candidates have noted that the take-home challenges can be open-ended and may not have a single correct solution. When tackling these challenges, focus on clearly identifying the problem, formulating a structured approach to your solution, and communicating your results effectively. This demonstrates not only your technical skills but also your ability to think critically and articulate your thought process.

Communicate Professionally and Follow Up

Throughout the interview process, maintain a professional demeanor and clear communication. Given the mixed reviews regarding the hiring process, it’s essential to follow up after your interviews. If you haven’t heard back within the timeframe they provided, a polite email can help keep you on their radar. However, be prepared for the possibility of delays or lack of communication, and remember that this reflects more on the company than on your candidacy.

Emphasize Remote Work Experience

If you have experience working remotely, be sure to highlight this during your interviews. Discuss how you manage your time, communicate with team members, and maintain productivity in a remote setting. This is particularly relevant as many companies, including Degreed, are adapting to flexible work environments.

By following these tailored tips, you can present yourself as a strong candidate who not only possesses the necessary technical skills but also aligns well with Degreed's culture and values. Good luck!

In this section, we’ll review the various interview questions that might be asked during a Data Engineer interview at Degreed. The interview process will likely focus on your technical skills, experience with data systems, and your ability to work collaboratively in a team environment. Be prepared to discuss your past projects, problem-solving approaches, and how you handle data-related challenges.

Technical Skills

1. Can you describe your experience with data warehousing solutions?

Understanding your familiarity with data warehousing is crucial, as it is a key component of data engineering.

How to Answer

Discuss specific data warehousing technologies you have used, the architecture you implemented, and any challenges you faced during the process.

Example

“I have worked extensively with Amazon Redshift and Google BigQuery. In my last project, I designed a data warehouse that integrated data from multiple sources, which improved our reporting capabilities. One challenge was optimizing query performance, which I addressed by implementing partitioning and indexing strategies.”

2. What ETL tools have you used, and how did you implement them in your projects?

ETL (Extract, Transform, Load) processes are fundamental to data engineering, and your experience with these tools will be evaluated.

How to Answer

Mention specific ETL tools you have experience with, describe how you used them in your projects, and highlight any improvements you made to the ETL process.

Example

“I have used Apache NiFi and Talend for ETL processes. In a recent project, I automated data extraction from various APIs using NiFi, which reduced manual effort by 70%. I also implemented data validation checks to ensure data quality before loading it into our data warehouse.”

3. How do you ensure data quality and integrity in your data pipelines?

Data quality is critical in data engineering, and interviewers will want to know your strategies for maintaining it.

How to Answer

Discuss specific techniques or tools you use to monitor and validate data quality throughout the data pipeline.

Example

“I implement data validation rules at each stage of the pipeline, using tools like Great Expectations. Additionally, I set up alerts for any anomalies detected in the data, allowing for quick remediation before the data is used for analysis.”

Programming and Scripting

4. What programming languages are you proficient in, and how have you applied them in your work?

Your programming skills are essential for a data engineer, and interviewers will want to know your level of expertise.

How to Answer

List the programming languages you are comfortable with and provide examples of how you have used them in data engineering tasks.

Example

“I am proficient in Python and SQL. I have used Python for data manipulation and analysis, leveraging libraries like Pandas and NumPy. In one project, I wrote a Python script to automate data cleaning, which significantly reduced processing time.”

5. Can you explain the importance of version control in data engineering?

Version control is vital for collaboration and maintaining code integrity, and your understanding of it will be assessed.

How to Answer

Discuss your experience with version control systems and how they have benefited your projects.

Example

“I use Git for version control, which allows me to track changes and collaborate effectively with my team. It has been particularly useful in managing code for our data pipelines, enabling us to roll back to previous versions if needed and maintain a clear history of changes.”

Problem-Solving and Project Management

6. Describe a challenging data engineering project you worked on. What was your role, and how did you overcome the challenges?

This question assesses your problem-solving skills and ability to work under pressure.

How to Answer

Provide a specific example of a project, the challenges you faced, and the steps you took to resolve them.

Example

“In a project to integrate a new data source, we faced significant latency issues. As the lead engineer, I analyzed the data flow and identified bottlenecks in our ETL process. I optimized the data transformation steps and implemented parallel processing, which improved the overall performance by 50%.”

7. How do you prioritize tasks when working on multiple data projects?

Time management and prioritization are key skills for a data engineer, especially when handling multiple projects.

How to Answer

Explain your approach to prioritizing tasks and how you ensure deadlines are met.

Example

“I use a combination of Agile methodologies and project management tools like Jira to prioritize tasks. I assess the impact and urgency of each task, focusing on high-impact projects first while ensuring that I communicate regularly with stakeholders to manage expectations.”

Collaboration and Communication

8. How do you communicate technical concepts to non-technical stakeholders?

Effective communication is essential in a collaborative environment, and your ability to convey complex ideas will be evaluated.

How to Answer

Discuss your strategies for simplifying technical jargon and ensuring understanding among non-technical team members.

Example

“I focus on using analogies and visual aids to explain technical concepts. For instance, when discussing data flow, I might compare it to a water pipeline, which helps non-technical stakeholders grasp the idea of data movement and bottlenecks.”

9. Can you provide an example of how you worked with a cross-functional team?

Collaboration with different teams is common in data engineering, and interviewers will want to know about your experience.

How to Answer

Share a specific instance where you collaborated with other teams, highlighting your role and the outcome.

Example

“I collaborated with the marketing team to develop a dashboard for tracking campaign performance. I gathered their requirements, designed the data model, and worked closely with them to ensure the dashboard met their needs. This collaboration resulted in a tool that improved their decision-making process significantly.”