The Zebra Data Engineer Interview Questions + Guide in 2025

The Zebra is a leading independent insurance comparison site dedicated to simplifying the insurance shopping experience for consumers.

In the role of Data Engineer at The Zebra, you will be integral to developing a robust data platform that supports the company's commitment to leveraging data for smarter business decisions. Key responsibilities include implementing scalable data pipelines, creating datasets for advanced reporting, and collaborating with engineers and analysts on data processing techniques. The ideal candidate will have a strong programming background, particularly in Python, SQL, and other relevant languages, along with experience in building scalable data warehouses and working with relational and NoSQL databases. A passion for problem-solving and the ability to thrive in a fast-paced environment that values diverse perspectives will make you an excellent fit for this position. This guide aims to equip you with the insights and knowledge necessary to excel in your interview for this role.

The interview process for a Data Engineer at The Zebra is designed to assess both technical skills and cultural fit within the organization. It typically unfolds in several stages, ensuring a comprehensive evaluation of candidates.

1. Initial Screening

The process begins with an initial phone screening, usually conducted by a technical recruiter. This 30-minute conversation focuses on your background, experience, and motivation for applying to The Zebra. The recruiter will also provide insights into the company culture and the specifics of the Data Engineer role. It's essential to be prepared to discuss your technical skills and how they align with the job requirements.

2. Technical Assessment

Following the initial screening, candidates are often required to complete a technical assessment. This may include a coding challenge that tests your proficiency in relevant programming languages such as Python or SQL. The assessment is designed to evaluate your problem-solving abilities and your understanding of data engineering concepts. Be ready to demonstrate your skills in building scalable data pipelines and working with databases.

3. Whiteboarding Session

Candidates who pass the technical assessment may be invited to a whiteboarding session with current engineers. This interactive segment allows you to showcase your thought process and technical skills in real-time. You may be asked to solve problems related to data processing, data access, and manipulation techniques. It's crucial to articulate your reasoning and approach during this session, as collaboration and communication are key components of the role.

4. Take-Home Challenge

In some cases, candidates will be given a take-home challenge that can take several hours to complete. This challenge typically involves building a data pipeline or creating datasets for reporting and analytics. The goal is to assess your ability to work independently and produce high-quality, reliable code. Make sure to manage your time effectively and present your solution clearly, as this will be part of the evaluation.

5. Panel Interview

The final stage of the interview process is a panel interview, which may consist of multiple rounds with various team members, including the hiring manager and other engineers. This segment can last several hours and will cover both technical and behavioral questions. Expect to discuss your past experiences, how you handle competing priorities, and your approach to finding data-driven solutions to business problems. This is also an opportunity for you to ask questions about the team dynamics and company culture.

As you prepare for your interview, consider the types of questions that may arise during these stages, particularly those that focus on your technical expertise and problem-solving abilities.

Here are some tips to help you excel in your interview.

Prepare for a Rigorous Process

The interview process at The Zebra can be extensive, often involving multiple stages such as coding assessments, whiteboarding tasks, and take-home challenges. To stand out, practice coding problems that reflect the skills required for the role, particularly in SQL and algorithms. Familiarize yourself with the types of data pipelines and data processing techniques you might be asked to discuss. Being well-prepared will not only help you perform better but also demonstrate your commitment to the role.

Showcase Your Technical Skills

Given the emphasis on SQL and algorithms, ensure you can confidently discuss your experience with these technologies. Be ready to explain your approach to building scalable data platforms and pipelines. If you have experience with data warehouses or big data technologies like Hadoop or Spark, prepare to share specific examples of how you've utilized these tools in past projects. Highlighting your technical expertise will be crucial in establishing your fit for the role.

Emphasize Collaboration and Communication

The Zebra values teamwork and collaboration, so be prepared to discuss how you have worked effectively with others in previous roles. Share examples of how you’ve collaborated with engineers and analysts to solve data-related challenges. Additionally, since the interview process may involve multiple interviewers, practice articulating your thoughts clearly and concisely to ensure you can engage effectively with each person.

Be Ready for Behavioral Questions

Expect to encounter behavioral questions that assess your problem-solving abilities and how you handle competing priorities. Reflect on past experiences where you successfully navigated challenges or conflicts in a team setting. Use the STAR (Situation, Task, Action, Result) method to structure your responses, ensuring you convey not just what you did, but the impact of your actions.

Understand the Company Culture

The Zebra prides itself on inclusivity and diversity, as reflected in their motto "All Stripes Welcome." Familiarize yourself with the company’s values and be prepared to discuss how your own values align with theirs. Show enthusiasm for their mission and express your desire to contribute to a positive and inclusive work environment. This alignment can set you apart as a candidate who not only has the technical skills but also fits well within the company culture.

Follow Up Thoughtfully

After your interviews, consider sending a thoughtful follow-up email to express your appreciation for the opportunity to interview and reiterate your interest in the role. Mention specific aspects of the conversation that resonated with you, which can help reinforce your enthusiasm and keep you top of mind as they make their decision.

By focusing on these areas, you can present yourself as a well-rounded candidate who is not only technically proficient but also a great cultural fit for The Zebra. Good luck!

In this section, we’ll review the various interview questions that might be asked during a Data Engineer interview at The Zebra. The interview process will likely focus on your technical skills, problem-solving abilities, and how you can contribute to building a reliable and scalable data platform. Be prepared to discuss your experience with data pipelines, databases, and programming languages, as well as your approach to collaboration and data-driven decision-making.

Technical Skills

1. Can you explain the process of building a data pipeline from scratch?

This question assesses your understanding of data pipeline architecture and your ability to implement it effectively.

How to Answer

Outline the steps involved in building a data pipeline, including data ingestion, processing, storage, and retrieval. Highlight any tools or technologies you would use and the importance of scalability and reliability.

Example

“To build a data pipeline from scratch, I would start by identifying the data sources and determining the best method for data ingestion, such as using APIs or batch processing. Next, I would process the data using tools like Apache Spark for transformation and cleaning. After that, I would store the data in a scalable data warehouse like Snowflake, ensuring that it is easily accessible for analytics. Finally, I would implement monitoring and logging to maintain the pipeline’s reliability.”

2. What experience do you have with SQL and how have you used it in your previous roles?

This question evaluates your proficiency with SQL, which is crucial for data manipulation and querying.

How to Answer

Discuss your experience with SQL, including specific tasks you have performed, such as writing complex queries, optimizing performance, or working with different database systems.

Example

“I have over two years of experience using SQL for data analysis and reporting. In my previous role, I wrote complex queries to extract insights from large datasets, optimized query performance by indexing tables, and collaborated with analysts to create dashboards that visualized key metrics.”

3. Describe a challenging data problem you faced and how you solved it.

This question tests your problem-solving skills and ability to handle real-world data challenges.

How to Answer

Provide a specific example of a data-related challenge, detailing the context, your approach to solving it, and the outcome.

Example

“In a previous project, we faced issues with data quality due to inconsistent formats across multiple sources. I initiated a data cleaning process using Python scripts to standardize the formats and implemented validation checks to ensure data integrity. This significantly improved the accuracy of our reports and decision-making.”

4. How do you ensure the scalability of a data system?

This question assesses your understanding of scalability and your ability to design systems that can grow with the business.

How to Answer

Discuss the principles of scalability, including horizontal and vertical scaling, and any specific technologies or architectures you would use to achieve it.

Example

“To ensure scalability, I focus on designing systems that can handle increased loads without significant performance degradation. I prefer using a microservices architecture, which allows for independent scaling of components. Additionally, I leverage cloud services like AWS to dynamically allocate resources based on demand.”

Collaboration and Communication

5. How would you approach working with data analysts and other engineers on a project?

This question evaluates your teamwork and communication skills, which are essential in a collaborative environment.

How to Answer

Emphasize the importance of clear communication, understanding project requirements, and being open to feedback.

Example

“I believe in fostering open communication with data analysts and engineers by holding regular meetings to discuss project goals and progress. I make it a point to actively listen to their needs and provide updates on any challenges I encounter. This collaborative approach ensures that we are all aligned and can effectively tackle any issues together.”

6. Can you describe a time when you had to explain a technical concept to a non-technical audience?

This question tests your ability to communicate complex ideas in an understandable way.

How to Answer

Provide an example where you successfully simplified a technical concept for a non-technical audience, focusing on your communication strategy.

Example

“During a project presentation, I had to explain our data processing workflow to stakeholders who were not familiar with technical jargon. I used visual aids and analogies to illustrate the process, breaking it down into simple steps. This helped them understand the value of our work and how it impacted their decisions.”

Data Technologies

7. What experience do you have with cloud data platforms like AWS or Google Cloud?

This question assesses your familiarity with cloud technologies, which are often used in data engineering.

How to Answer

Discuss your experience with specific cloud platforms, the services you have used, and how they contributed to your projects.

Example

“I have worked extensively with AWS, utilizing services like S3 for data storage and Redshift for data warehousing. In one project, I set up an ETL process using AWS Glue to automate data ingestion and transformation, which significantly reduced manual effort and improved data availability for analysis.”

8. How do you handle data security and compliance in your projects?

This question evaluates your understanding of data security practices and regulatory compliance.

How to Answer

Discuss the importance of data security, the measures you take to protect sensitive information, and your knowledge of relevant regulations.

Example

“I prioritize data security by implementing encryption for data at rest and in transit. I also ensure that access controls are in place to restrict data access to authorized personnel only. Additionally, I stay informed about regulations like GDPR and CCPA to ensure compliance in all my projects.”