23andMe Data Engineer Interview Questions + Guide in 2025

23andMe is a pioneering personal genomics and biotechnology company that empowers individuals to access and understand their genetic information.

The role of a Data Engineer at 23andMe is integral to transforming data into actionable insights that can enhance customer experiences and drive business strategies. Key responsibilities include designing and maintaining scalable data pipelines, ensuring data integrity, and collaborating with cross-functional teams to support various business initiatives. A successful Data Engineer at 23andMe will possess a strong proficiency in big data technologies, data modeling, and ETL processes, along with experience in programming languages such as Python or SQL. Ideal candidates should demonstrate a problem-solving mindset, excellent communication skills, and a passion for utilizing data to influence product development and customer engagement.

This guide aims to equip you with the knowledge and confidence to excel in your interview by providing insights into the expectations and culture at 23andMe, ultimately enhancing your chances of securing the role.

The interview process for a Data Engineer role at 23andMe is structured to assess both technical skills and cultural fit within the team. It typically consists of several stages, each designed to evaluate different aspects of a candidate's qualifications and compatibility with the company's values.

1. Initial Phone Screen

The process begins with an initial phone screen, usually conducted by a recruiter or the hiring manager. This conversation lasts about 30-60 minutes and focuses on your background, interest in the company, and relevant projects. Expect to discuss your experience with data engineering concepts, technologies, and your motivation for applying to 23andMe.

2. Technical Phone Interview

If you pass the initial screen, you will be invited to a technical phone interview. This stage often includes coding challenges and questions related to data structures and algorithms. Candidates may be asked to solve problems in real-time, demonstrating their thought process and technical proficiency. Be prepared for questions that assess your understanding of big data technologies and your approach to solving complex engineering problems.

3. Take-Home Assignment

Following the technical phone interview, candidates may be required to complete a take-home assignment. This assignment typically involves a data engineering problem relevant to the work at 23andMe. It allows candidates to showcase their skills in a practical context and may require a presentation of the solution in a subsequent interview.

4. Onsite Interviews

The final stage of the interview process is the onsite interviews, which can last several hours. This phase usually consists of multiple one-on-one interviews with team members, including technical and behavioral assessments. Expect to engage in discussions about your past projects, problem-solving approaches, and how you would handle various scenarios in a team setting. Technical interviews may involve whiteboarding exercises, system design questions, and coding challenges.

5. Cultural Fit Assessment

Throughout the interview process, 23andMe places a strong emphasis on cultural fit. Interviewers will assess how well you align with the company's values and work environment. Be prepared to discuss your teamwork experiences, how you handle conflicts, and your approach to collaboration with stakeholders.

As you prepare for your interviews, consider the types of questions that may arise in each of these stages.

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

Embrace the Conversational Nature of Interviews

At 23andMe, interviews tend to feel more like conversations than formal interrogations. Approach each interview as an opportunity to engage with your interviewers. Be prepared to discuss your past experiences, skills, and projects in a narrative format. This will not only showcase your qualifications but also allow you to connect with the interviewers on a personal level. Remember, they are genuinely interested in getting to know you, so don’t hesitate to share your thoughts and insights.

Prepare for Behavioral Questions

Expect a significant number of behavioral questions that assess your problem-solving approach and how you interact with various stakeholders. Prepare specific examples from your past experiences that demonstrate your ability to handle challenges, collaborate with teams, and communicate effectively. Use the STAR (Situation, Task, Action, Result) method to structure your responses, ensuring you convey the impact of your actions clearly.

Showcase Your Technical Skills

As a Data Engineer, you will likely face technical questions that assess your knowledge of data structures, algorithms, and relevant technologies. Brush up on your skills in SQL, Python, and any other tools mentioned in the job description. Be ready to discuss your past projects in detail, focusing on the technical challenges you faced and how you overcame them. This will not only demonstrate your expertise but also your ability to apply your knowledge in real-world scenarios.

Understand the Company Culture

23andMe values a collaborative and down-to-earth culture. During your interviews, express your enthusiasm for working in such an environment. Highlight experiences where you thrived in team settings or contributed to a positive workplace culture. This will help you align yourself with the company’s values and show that you would be a good cultural fit.

Be Prepared for a Take-Home Assignment

Some candidates have mentioned a take-home assignment as part of the interview process. If this is applicable to you, treat it seriously and approach it as an opportunity to showcase your problem-solving skills. Ensure that your submission is well-structured and clearly communicates your thought process. This is your chance to demonstrate not just your technical abilities but also your creativity and analytical thinking.

Follow Up Professionally

After your interviews, consider sending a thank-you email to express your appreciation for the opportunity to interview. This is a chance to reiterate your interest in the role and the company. However, be mindful of the feedback process; some candidates have noted a lack of communication post-interview. If you don’t hear back in a reasonable timeframe, a polite follow-up can help keep you on their radar.

Stay Positive and Resilient

Lastly, maintain a positive attitude throughout the process. While some candidates have reported challenges with communication and feedback, focus on the aspects of the interview that you can control. Approach each interaction with confidence and professionalism, and remember that every interview is a learning experience, regardless of the outcome.

By following these tips, you can position yourself as a strong candidate for the Data Engineer role at 23andMe. Good luck!

Experience and Background

1. Describe a time you had to solve a technical challenge.

This question aims to assess your problem-solving skills and how you approach technical difficulties in your work.

How to Answer

Focus on a specific challenge you faced, the steps you took to resolve it, and the outcome. Highlight your analytical skills and ability to work under pressure.

Example

“In my previous role, I encountered a significant data pipeline failure that affected our reporting. I quickly diagnosed the issue, which was a misconfiguration in our ETL process. I collaborated with the team to implement a fix and set up monitoring to prevent future occurrences, which improved our data reliability by 30%.”

2. Walk me through one of your past projects in detail.

This question allows you to showcase your experience and technical expertise.

How to Answer

Select a project that is relevant to the role and discuss your specific contributions, the technologies used, and the impact of the project.

Example

“I worked on a project to optimize our data warehouse. I led the migration from a traditional SQL database to a more scalable NoSQL solution. This transition reduced query times by 50% and allowed us to handle larger datasets more efficiently.”

3. How would you find out what customers want?

This question assesses your ability to gather requirements and understand user needs.

How to Answer

Discuss methods you would use to gather customer insights, such as surveys, interviews, or data analysis.

Example

“I would start by analyzing existing customer feedback and usage data to identify trends. Additionally, I would conduct user interviews to gain qualitative insights, ensuring that the product aligns with customer expectations.”

4. Explain a time you experienced a conflict with a team member on a project and how you solved it.

This question evaluates your interpersonal skills and ability to work collaboratively.

How to Answer

Describe the conflict, how you approached the situation, and the resolution. Emphasize your communication and negotiation skills.

Example

“During a project, a colleague and I disagreed on the approach to data modeling. I initiated a meeting where we could both present our perspectives. By focusing on the project goals and being open to compromise, we reached a solution that incorporated both of our ideas, ultimately enhancing the project.”

Technical Skills

1. What is your approach to experiment design?

This question tests your understanding of data-driven decision-making.

How to Answer

Discuss the key elements of experiment design, including hypothesis formulation, control groups, and metrics for success.

Example

“I start by clearly defining the hypothesis and objectives of the experiment. I ensure that I have a control group to compare results and select appropriate metrics to measure success. After conducting the experiment, I analyze the data to draw actionable insights.”

2. How does [specific technology] work?

This question assesses your technical knowledge of relevant tools and technologies.

How to Answer

Provide a concise explanation of the technology, its purpose, and how it fits into the data engineering landscape.

Example

“Apache Kafka is a distributed streaming platform that allows for the real-time processing of data streams. It works by publishing and subscribing to streams of records, similar to a message queue, which enables efficient data integration across various systems.”

3. Can you explain the difference between SQL and NoSQL databases?

This question evaluates your understanding of database technologies.

How to Answer

Discuss the key differences in structure, scalability, and use cases for both types of databases.

Example

“SQL databases are relational and use structured query language for defining and manipulating data, making them ideal for complex queries and transactions. In contrast, NoSQL databases are non-relational and can handle unstructured data, providing greater flexibility and scalability for large datasets.”

4. Describe your experience with data structures and algorithms.

This question gauges your foundational knowledge in computer science.

How to Answer

Highlight your experience with various data structures and algorithms, and how you have applied them in real-world scenarios.

Example

“I have extensive experience with data structures such as arrays, linked lists, and trees. For instance, I implemented a binary search tree for a project that required efficient data retrieval, which improved performance by reducing search times significantly.”

5. What is your experience with big data technologies?

This question assesses your familiarity with tools and frameworks used in big data processing.

How to Answer

Discuss specific technologies you have worked with, your role in projects, and the outcomes achieved.

Example

“I have worked with Hadoop and Spark for processing large datasets. In one project, I used Spark to analyze user behavior data, which allowed us to identify key trends and improve our marketing strategies, resulting in a 20% increase in user engagement.”