Notion Labs Data Engineer Interview Questions + Guide in 2025

Notion Labs is committed to empowering individuals and teams by providing a flexible software platform that enables them to tailor their digital tools for solving various challenges.

The Data Engineer role at Notion Labs is vital for building and maintaining the foundational datasets and pipelines that drive key business decisions. As a Data Engineer, you will be responsible for defining processes and ETL infrastructure to ensure data is readily available and effectively utilized across various departments, including product, marketing, sales, and finance. You will collaborate closely with data scientists and stakeholders to understand their data needs, design scalable pipelines, and automate workflows that enhance operational efficiency. A strong background in SQL, experience with cloud data solutions, and a passion for solving complex data problems are essential to excel in this role. The ideal candidate will be a self-starter who can communicate effectively, prioritize tasks, and demonstrate technical expertise in data modeling and analytics.

This guide will help you prepare by equipping you with insights into the expectations and skills needed for the Data Engineer position at Notion Labs, ultimately giving you an edge in the interview process.

The interview process for a Data Engineer role at Notion Labs is structured and thorough, designed to assess both technical skills and cultural fit. Candidates can expect a series of interviews that evaluate their experience, problem-solving abilities, and alignment with Notion's values.

1. Initial Recruiter Call

The process typically begins with a 30-minute introductory call with a recruiter. This conversation serves to gauge your interest in the role and the company, as well as to discuss your background and experiences. The recruiter will also provide insights into Notion's culture and the specifics of the Data Engineer position. It's an opportunity for you to ask questions about the company and the role.

2. Technical Screening

Following the initial call, candidates will undergo a technical screening, which may involve a live coding challenge or a take-home project. This stage focuses on your ability to solve practical problems relevant to the role, such as building data pipelines or working with SQL. Expect to demonstrate your coding skills and your understanding of data engineering concepts, including data manipulation and ETL processes.

3. Onsite Interviews

The onsite interview typically consists of multiple rounds, often including both technical and behavioral interviews. Candidates can expect to engage in coding exercises, system design discussions, and project deep-dives. Interviewers may include data engineers, product managers, and other cross-functional team members. Each interview is designed to assess your technical expertise, problem-solving skills, and how well you collaborate with others.

4. Leadership Interview

In the final stages of the interview process, candidates may have a conversation with a member of the leadership team, such as the Head of Data or even the CEO. This interview focuses on your long-term vision, cultural fit, and how you can contribute to Notion's mission. It’s an opportunity for you to showcase your passion for data engineering and your alignment with the company's values.

5. Reference Check

After successfully completing the interview rounds, candidates will typically undergo a reference check. This step involves contacting previous employers or colleagues to verify your work history and performance.

As you prepare for your interviews, be ready to discuss your past experiences and how they relate to the role at Notion. Here are some of the interview questions that candidates have encountered during the process.

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

Understand the Interview Structure

Familiarize yourself with Notion's interview process, which typically includes a recruiter call, a technical screening, and multiple rounds of interviews focusing on coding, systems design, and behavioral questions. Knowing the structure will help you prepare effectively and manage your time during the interview.

Prepare for Technical Challenges

Expect to face practical coding challenges that reflect real-world scenarios rather than abstract LeetCode problems. Brush up on your SQL skills, as well as your knowledge of data manipulation in Python or other relevant languages. Be ready to demonstrate your ability to build and monitor data pipelines, as well as your understanding of data models and analytics use cases.

Showcase Your Experience with Data Tools

Highlight your hands-on experience with cloud platforms (AWS, GCP, Azure) and data storage solutions (Snowflake, Redshift, etc.). Be prepared to discuss specific projects where you built scalable data solutions or integrated various data systems. This will demonstrate your technical expertise and your ability to contribute to Notion's data engineering goals.

Emphasize Collaboration and Communication

Notion values collaboration, so be ready to discuss how you've worked with cross-functional teams in the past. Share examples of how you gathered requirements from stakeholders and communicated technical solutions effectively. This will show that you can thrive in a team-oriented environment and contribute to Notion's mission of democratizing data access.

Be Authentic and Engaged

During the interview, be yourself and engage with your interviewers. Notion's culture emphasizes empathy and collaboration, so showing genuine interest in the team and the work can set you apart. Ask thoughtful questions about the role, the team dynamics, and the company's future direction to demonstrate your enthusiasm for the position.

Prepare for Behavioral Questions

Expect behavioral questions that assess your problem-solving abilities and how you handle ambiguity. Use the STAR (Situation, Task, Action, Result) method to structure your responses, focusing on specific examples from your past experiences. This will help you convey your thought process and the impact of your actions clearly.

Follow Up Thoughtfully

After the interview, consider sending a thank-you note to express your appreciation for the opportunity to interview. Mention specific topics discussed during the interview to reinforce your interest in the role and the company. This small gesture can leave a positive impression and keep you top of mind for the hiring team.

By following these tips, you'll be well-prepared to showcase your skills and fit for the Data Engineer role at Notion. Good luck!

In this section, we’ll review the various interview questions that might be asked during a Data Engineer interview at Notion Labs. The interview process will likely assess your technical skills, problem-solving abilities, and cultural fit within the company. Be prepared to discuss your past experiences, technical knowledge, and how you approach data challenges.

Technical Skills

1. Can you describe your experience with ETL processes and the tools you have used?

Understanding your experience with ETL processes is crucial, as this role involves building and maintaining data pipelines.

How to Answer

Discuss specific ETL tools you have used, the types of data you have worked with, and any challenges you faced during the process.

Example

“I have extensive experience with ETL processes using tools like Apache Airflow and AWS Glue. In my previous role, I built a pipeline that integrated data from multiple sources, which improved our reporting efficiency by 30%. I faced challenges with data quality, which I addressed by implementing validation checks at each stage of the pipeline.”

2. How do you ensure data quality and integrity in your datasets?

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

How to Answer

Explain your approach to data validation, error handling, and monitoring data quality over time.

Example

“I implement data validation checks at various stages of the ETL process, including schema validation and data type checks. Additionally, I set up monitoring alerts to catch anomalies in real-time, which allows us to address issues before they impact reporting.”

3. Describe a complex data problem you solved in your previous role.

This question assesses your problem-solving skills and ability to handle complex data challenges.

How to Answer

Provide a specific example, detailing the problem, your approach, and the outcome.

Example

“In my last position, we faced performance issues with our reporting queries due to large dataset sizes. I optimized our data model by implementing partitioning and indexing strategies, which reduced query times by over 50%, significantly improving our reporting capabilities.”

4. What is your experience with SQL, and can you provide an example of a complex query you wrote?

SQL proficiency is essential for a Data Engineer, and interviewers will want to gauge your skills.

How to Answer

Discuss your SQL experience and walk through a complex query you’ve written, explaining its purpose and structure.

Example

“I have over five years of experience with SQL, and I often write complex queries involving multiple joins and window functions. For instance, I created a query to analyze customer churn by joining user activity logs with subscription data, which helped the marketing team identify at-risk customers.”

5. How do you approach designing a data model for a new project?

This question evaluates your understanding of data modeling principles and your design process.

How to Answer

Outline your approach to data modeling, including requirements gathering, schema design, and considerations for scalability.

Example

“When designing a data model, I start by gathering requirements from stakeholders to understand their needs. I then create an initial schema using dimensional modeling principles, ensuring it can scale as data volume grows. I also consider how the data will be queried to optimize performance.”

Behavioral Questions

1. Tell me about a time you had to work with a cross-functional team.

Collaboration is key in data engineering, and this question assesses your teamwork skills.

How to Answer

Share a specific example of a project where you collaborated with other teams, highlighting your role and contributions.

Example

“I worked on a project with the marketing and sales teams to integrate their data into our reporting system. I facilitated meetings to gather requirements and ensured that the data we provided met their needs. This collaboration resulted in a more comprehensive view of customer interactions, which improved our sales strategies.”

2. How do you handle ambiguity in a project?

Data engineers often face ambiguous situations, and interviewers want to know how you navigate them.

How to Answer

Discuss your approach to clarifying requirements and making decisions in uncertain situations.

Example

“When faced with ambiguity, I prioritize gathering as much information as possible from stakeholders. I ask clarifying questions and conduct research to understand the context better. If necessary, I make informed assumptions and document them, ensuring that I can adjust as more information becomes available.”

3. Describe a project you are most proud of and why.

This question allows you to showcase your achievements and what you value in your work.

How to Answer

Choose a project that highlights your skills and contributions, explaining why it was significant to you.

Example

“I’m particularly proud of a project where I built a real-time analytics dashboard for our product team. It involved integrating data from various sources and implementing a user-friendly interface. The dashboard provided insights that led to a 20% increase in user engagement, which was incredibly rewarding to see.”

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

Time management is crucial in a fast-paced environment, and interviewers want to know your strategies.

How to Answer

Explain your prioritization process and any tools or methods you use to stay organized.

Example

“I use a combination of project management tools and regular check-ins with my team to prioritize tasks. I assess the impact and urgency of each project, focusing on high-impact tasks first. This approach ensures that I meet deadlines while maintaining the quality of my work.”

5. Why do you want to work at Notion?

This question assesses your motivation for applying and your alignment with the company’s values.

How to Answer

Share your enthusiasm for Notion’s mission and how your skills align with their goals.

Example

“I admire Notion’s mission to empower users to tailor their software solutions. I believe my experience in building scalable data pipelines aligns perfectly with your goals of democratizing data access. I’m excited about the opportunity to contribute to a product that has such a positive impact on users.”