The RealReal Data Engineer Interview Questions + Guide in 2025

The RealReal is the world's largest online marketplace for authenticated, resale luxury goods, committed to sustainability and the circular economy.

As a Data Engineer at The RealReal, you will play a pivotal role in designing and developing robust, scalable data architectures and MLOps solutions. Your core responsibilities will include building and maintaining high-performance data infrastructure to support real-time and batch processing of large datasets, creating reliable services and APIs for seamless data interaction, and collaborating with cross-functional teams to address their data needs. You will also be responsible for monitoring and managing ML systems, ensuring their efficient operation for model development and evaluation.

Key skills for this role include strong programming expertise in languages such as Python, Java, or Scala, alongside experience with cloud platforms like GCP and AWS. Familiarity with ML frameworks and tools, data pipelines, and containerization techniques will also greatly benefit your candidacy. As an ideal candidate, you should demonstrate excellent communication and collaboration skills, a passion for innovation, and the ability to work independently while contributing to team goals.

This guide will help you prepare for your interview by equipping you with insights into the expectations and culture at The RealReal, as well as the technical and interpersonal skills you need to highlight during your discussions.

The interview process for a Data Engineer position at The RealReal is designed to assess both technical skills and cultural fit within the team. It typically consists of several stages, each focusing on different aspects of the candidate's qualifications and experiences.

1. Initial Phone Screen

The process begins with an initial phone screen, usually conducted by a recruiter. This conversation lasts about 30 minutes and serves to gauge your interest in the role and the company. The recruiter will ask about your background, relevant experiences, and motivations for applying. This is also an opportunity for you to ask questions about the company culture and the specifics of the Data Engineering team.

2. Technical Assessment

Following the initial screen, candidates are often required to complete a technical assessment, which may be conducted through an online platform like HackerRank. This assessment typically includes coding challenges that focus on data structures, algorithms, and problem-solving skills. Expect questions that range from easy to medium difficulty, often reflecting real-world scenarios you might encounter in the role.

3. Technical Interviews

Candidates who pass the technical assessment will move on to a series of technical interviews, usually consisting of two rounds. Each interview lasts about an hour and includes a mix of behavioral questions and coding exercises. You may be asked to engage in pair programming or solve coding problems in languages relevant to the role, such as Python or Ruby on Rails. Interviewers will assess your ability to think critically and communicate your thought process clearly.

4. Behavioral Interview

After the technical rounds, candidates typically participate in a behavioral interview. This session focuses on your past experiences and how they align with The RealReal's values. Expect to answer questions using the STAR (Situation, Task, Action, Result) method, discussing your career goals and how you handle challenges in a team environment.

5. System Design and Culture Fit

The final round often involves a system design interview, where you will be asked to design a data architecture or pipeline that meets specific requirements. This is an opportunity to showcase your understanding of scalable data solutions and MLOps practices. Additionally, interviewers will assess your fit within the company culture, discussing your values and how they align with The RealReal's mission.

As you prepare for these interviews, it's essential to be ready for a variety of questions that will test both your technical expertise and your ability to collaborate effectively with cross-functional teams.

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

Embrace the Relaxed Environment

The RealReal is known for its friendly and relaxed atmosphere. Approach your interview with a calm demeanor and be open to engaging in friendly conversation. This will not only help you feel more comfortable but also allow the interviewers to see your personality and how you might fit into their team culture. Remember, they value collaboration and a positive work environment, so showcasing your interpersonal skills can be a significant advantage.

Prepare for Problem-Solving Questions

Expect a strong focus on problem-solving skills during your interviews. Brush up on coding challenges, particularly those involving recursion and array methods, as these have been common in past interviews. Practice coding problems on platforms like LeetCode, especially those categorized as easy to medium difficulty. Be ready to explain your thought process clearly and concisely, as interviewers appreciate candidates who can articulate their reasoning.

Showcase Your Technical Expertise

As a Data Engineer, you will be expected to demonstrate your technical skills, particularly in programming languages like Python, Java, or Scala. Be prepared to discuss your experience with cloud platforms, especially GCP, and your familiarity with data processing frameworks. Highlight any projects where you built scalable data architectures or worked with machine learning frameworks. Providing specific examples of your work will help illustrate your capabilities and how they align with the role.

Engage in Pair Programming

Some interviews may include a pair programming exercise, which is a great opportunity to demonstrate your collaborative skills. Approach this with a mindset of teamwork; communicate your thought process and be open to feedback. This not only shows your technical skills but also your ability to work well with others, which is crucial in a cross-functional team environment.

Prepare for Behavioral Questions

Expect to encounter behavioral questions that assess your long-term goals and how you handle challenges. Use the STAR (Situation, Task, Action, Result) method to structure your responses. Reflect on your past experiences and be ready to discuss how they have shaped your career path and prepared you for this role. This will help interviewers gauge your fit within the company culture and your alignment with their values.

Understand the Company’s Mission

The RealReal is committed to sustainability and the circular economy. Familiarize yourself with their mission and values, and be prepared to discuss why you want to work there. Articulating your passion for their goals and how your skills can contribute to their mission will resonate well with the interviewers.

Be Ready for System Design Discussions

In the final rounds, you may face system design questions. Prepare to discuss how you would design scalable data systems and the considerations you would take into account, such as data schemas, monitoring, and debugging. This is your chance to showcase your strategic thinking and technical depth, so be thorough in your explanations.

Follow Up Thoughtfully

After your interviews, consider sending a thoughtful follow-up message to express your appreciation for the opportunity and reiterate your interest in the role. This not only demonstrates professionalism but also keeps you top of mind as they make their decisions.

By following these tips and preparing thoroughly, you will position yourself as a strong candidate for the Data Engineer role at The RealReal. Good luck!

In this section, we’ll review the various interview questions that might be asked during a Data Engineer interview at The RealReal. The interview process will likely focus on your technical skills, problem-solving abilities, and your understanding of data architecture and MLOps. Be prepared to discuss your experience with data pipelines, cloud platforms, and machine learning frameworks, as well as your approach to collaboration and mentorship.

Technical Skills

1. Can you describe your experience with building data pipelines and ETL processes?

This question aims to assess your hands-on experience with data engineering tasks.

How to Answer

Discuss specific projects where you designed and implemented data pipelines, highlighting the tools and technologies you used.

Example

“In my previous role, I built a data pipeline using Apache Airflow to automate the ETL process for our sales data. This involved extracting data from various sources, transforming it to fit our analytical needs, and loading it into a Snowflake data warehouse. The pipeline improved our data processing time by 30%.”

2. What cloud platforms have you worked with, and how have you utilized them in your projects?

This question evaluates your familiarity with cloud technologies, particularly GCP or AWS.

How to Answer

Mention specific cloud services you have used and how they contributed to your data engineering tasks.

Example

“I have extensive experience with Google Cloud Platform, particularly BigQuery for data warehousing and Cloud Functions for serverless computing. In a recent project, I used BigQuery to analyze large datasets, which allowed our team to generate insights quickly and efficiently.”

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

This question tests your problem-solving skills and technical acumen.

How to Answer

Provide a specific example of a technical challenge, the steps you took to resolve it, and the outcome.

Example

“While working on a data migration project, we encountered performance issues with our ETL process. I identified bottlenecks in our data transformation steps and optimized them by implementing parallel processing using Apache Spark, which significantly reduced the processing time.”

4. How do you ensure the reliability and scalability of your data systems?

This question assesses your understanding of best practices in data engineering.

How to Answer

Discuss strategies you employ to maintain system reliability and scalability, such as monitoring, testing, and architecture design.

Example

“I implement monitoring tools like Prometheus to track system performance and set up alerts for any anomalies. Additionally, I design data architectures with scalability in mind, using microservices and containerization with Docker to ensure that our systems can handle increased loads seamlessly.”

5. What experience do you have with machine learning frameworks?

This question gauges your familiarity with ML frameworks and their integration into data engineering.

How to Answer

Mention specific frameworks you have used and how they relate to your data engineering work.

Example

“I have worked with TensorFlow and PyTorch for building machine learning models. In a recent project, I collaborated with data scientists to deploy a model using TensorFlow Serving, which allowed us to efficiently serve predictions in real-time.”

Behavioral Questions

1. Describe a time when you had to collaborate with cross-functional teams.

This question evaluates your teamwork and communication skills.

How to Answer

Share an example that highlights your ability to work with different teams and how you contributed to a successful outcome.

Example

“In my last position, I worked closely with data scientists and product managers to develop a new analytics dashboard. I facilitated regular meetings to ensure everyone was aligned on the project goals and timelines, which ultimately led to a successful launch that met user needs.”

2. How do you prioritize your tasks when working on multiple projects?

This question assesses your time management and organizational skills.

How to Answer

Explain your approach to prioritization and how you manage competing deadlines.

Example

“I use a combination of project management tools and agile methodologies to prioritize my tasks. I assess the impact and urgency of each project and communicate with stakeholders to ensure alignment on priorities, which helps me stay focused and productive.”

3. What are your long-term career goals, and how does this role fit into them?

This question helps the interviewer understand your career aspirations and commitment to the role.

How to Answer

Discuss your professional goals and how the position aligns with your career path.

Example

“My long-term goal is to become a lead data engineer, focusing on MLOps and data architecture. This role at The RealReal offers the opportunity to work on innovative data solutions and collaborate with talented professionals, which is essential for my growth in this field.”

4. Can you give an example of how you mentored a team member?

This question evaluates your leadership and mentoring abilities.

How to Answer

Share a specific instance where you provided guidance or support to a colleague.

Example

“I mentored a junior data engineer who was struggling with SQL queries. I organized a series of one-on-one sessions where I shared best practices and provided hands-on exercises. Over time, I saw significant improvement in their skills, and they became a valuable contributor to our team.”

5. Why do you want to work at The RealReal?

This question assesses your motivation and fit for the company culture.

How to Answer

Express your enthusiasm for the company’s mission and how your values align with theirs.

Example

“I admire The RealReal’s commitment to sustainability and the circular economy. I believe that my skills in data engineering can contribute to innovative solutions that enhance the customer experience while supporting these values.”