Figma Data Engineer Interview Questions + Guide in 2025

Figma is revolutionizing the design process by making it accessible to all through collaborative tools that enhance productivity across teams.

As a Data Engineer at Figma, you will play a pivotal role in owning and scaling the data pipelines that support the company's mission of efficient design and product development. You will collaborate closely with Data Science and Data Infrastructure teams, as well as various business stakeholders in sales, marketing, and finance, to ensure timely and reliable data access. Your key responsibilities will include developing scalable data pipelines, optimizing core data models, and establishing best practices for analytics and modeling. The ideal candidate is someone who is passionate about data systems, can communicate complex concepts to diverse audiences, and possesses strong problem-solving abilities. You should have a solid background in SQL and Python, along with familiarity in tools such as Snowflake, dbt, and Dagster.

This guide aims to equip you with the insights needed to excel in your Figma Data Engineer interview, providing you with an edge over other candidates by emphasizing the skills and experiences that align with Figma's values and operational needs.

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

1. Initial Recruiter Call

The process begins with a 30-minute phone call with a recruiter. This conversation serves as an introduction to Figma, where the recruiter will discuss the company culture, the role's expectations, and the overall interview process. Candidates will have the opportunity to share their background, experiences, and motivations for applying, allowing the recruiter to gauge fit and interest.

2. Technical Screen

Following the initial call, candidates will participate in a technical screening interview, which usually lasts about an hour. This interview is conducted via a live coding platform, where candidates are asked to solve coding problems relevant to the role. The questions often focus on SQL and Python, as well as data manipulation and pipeline construction. Candidates should be prepared for practical coding exercises that reflect real-world scenarios they might encounter at Figma.

3. Hiring Manager Interview

The next step typically involves a conversation with the hiring manager. This interview focuses on the candidate's past experiences, technical skills, and how they align with the team's goals. Candidates may be asked to discuss specific projects they have worked on, their problem-solving approaches, and how they collaborate with cross-functional teams. This is also an opportunity for candidates to ask questions about the team dynamics and expectations.

4. Onsite Interviews

If the candidate successfully passes the previous stages, they will be invited to a virtual onsite interview, which can consist of multiple rounds. These rounds usually include: - Technical Interviews: Candidates will face several technical challenges, including coding exercises and system design questions. These interviews assess the candidate's ability to build and maintain scalable data pipelines and their understanding of data modeling methodologies. - Behavioral Interviews: These sessions evaluate the candidate's soft skills, such as communication, teamwork, and cultural fit within Figma. Candidates should be prepared to discuss how they handle challenges, work with stakeholders, and contribute to a collaborative environment. - Deep Dive into Past Projects: Candidates may be asked to present a detailed overview of a significant project they have worked on, explaining their role, the challenges faced, and the outcomes achieved.

Throughout the interview process, candidates are encouraged to demonstrate their problem-solving skills, creativity, and ability to communicate complex ideas clearly.

As you prepare for your interview, it's essential to familiarize yourself with the types of questions that may arise during each stage.

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

Understand the Company Culture

Figma values collaboration, creativity, and a growth mindset. Familiarize yourself with their mission to make design accessible to all and how they approach teamwork. During the interview, demonstrate your alignment with these values by sharing examples of how you've collaborated with cross-functional teams or contributed to a culture of learning and development in your previous roles.

Prepare for Technical Challenges

Expect technical interviews to focus on real-world scenarios relevant to Figma's work. Brush up on your SQL and Python skills, as well as your understanding of data modeling and ETL processes. Practice coding problems that are not just algorithmic but also applicable to data engineering tasks, such as building scalable data pipelines or optimizing data models. Be ready to explain your thought process clearly and concisely as you work through these problems.

Communicate Effectively

Strong communication skills are essential for this role, as you'll be working with various stakeholders. Practice articulating complex technical concepts in simple terms. During the interview, ask clarifying questions if you don't understand something, and be sure to summarize your understanding of the problem before diving into solutions. This shows that you are engaged and ensures that you are on the right track.

Showcase Problem-Solving Skills

Figma looks for candidates who can balance quick, scrappy solutions with more robust, long-term strategies. Be prepared to discuss past experiences where you had to make these decisions. Highlight your judgment and creative problem-solving skills by providing specific examples of challenges you faced and how you approached them.

Be Ready for Behavioral Questions

Expect behavioral questions that assess your fit within the team and company culture. Use the STAR (Situation, Task, Action, Result) method to structure your responses. Reflect on your past experiences and be ready to discuss how you've handled challenges, worked with diverse teams, and contributed to successful projects.

Follow Up Thoughtfully

After the interview, send a thank-you note to your interviewers. Use this opportunity to reiterate your enthusiasm for the role and the company, and mention any specific points from the interview that resonated with you. This not only shows your appreciation but also reinforces your interest in the position.

By preparing thoroughly and demonstrating your alignment with Figma's values and expectations, you'll position yourself as a strong candidate for the Data Engineer role. Good luck!

In this section, we’ll review the various interview questions that might be asked during a Data Engineer interview at Figma. The interview process will likely assess your technical skills, problem-solving abilities, and your capacity to communicate effectively with cross-functional teams. Be prepared to demonstrate your knowledge of data pipelines, SQL, Python, and your understanding of data modeling and analytics.

Technical Skills

1. Can you explain how you would design a scalable data pipeline for a new feature at Figma?

This question assesses your understanding of data architecture and pipeline design.

How to Answer

Discuss the components of a data pipeline, including data ingestion, processing, storage, and retrieval. Highlight your approach to scalability and reliability.

Example

"I would start by identifying the data sources and the frequency of data updates. Then, I would use a cloud-based ETL tool to ingest the data, process it using Python scripts, and store it in a Snowflake database. I would ensure that the pipeline can handle increased loads by implementing partitioning and indexing strategies."

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

This question evaluates your problem-solving skills and experience.

How to Answer

Provide a specific example, detailing the problem, your approach, and the outcome. Emphasize your analytical skills and creativity.

Example

"In a previous role, I encountered a significant delay in data processing due to inefficient queries. I analyzed the query execution plans and identified bottlenecks. By optimizing the SQL queries and adding appropriate indexes, I reduced processing time by 40%, which significantly improved reporting efficiency."

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

This question tests your understanding of data integrity and validation techniques.

How to Answer

Discuss the methods you use to validate data, such as checksums, data profiling, and automated testing.

Example

"I implement data validation checks at various stages of the pipeline. For instance, I use checksums to verify data integrity during ingestion and perform data profiling to identify anomalies. Additionally, I set up alerts for any discrepancies to ensure timely resolution."

4. What experience do you have with ETL tools, and which do you prefer?

This question gauges your familiarity with ETL processes and tools.

How to Answer

Mention specific ETL tools you have used, your experience with them, and why you prefer one over the others.

Example

"I have extensive experience with dbt and Dagster for ETL processes. I prefer dbt for its ability to manage transformations in a modular way, which enhances maintainability. Dagster's orchestration capabilities also allow for better monitoring and error handling."

5. Can you explain the concept of data modeling and its importance?

This question assesses your understanding of data modeling methodologies.

How to Answer

Define data modeling and discuss its significance in creating efficient databases and ensuring data integrity.

Example

"Data modeling is the process of creating a conceptual representation of data structures and relationships. It is crucial because it helps in designing databases that are efficient and scalable, ensuring that data can be accessed and analyzed effectively."

SQL and Python Proficiency

1. Write a SQL query to find the top 10 customers by revenue.

This question tests your SQL skills and ability to write efficient queries.

How to Answer

Demonstrate your SQL knowledge by writing a clear and efficient query.

Example

"SELECT customer_id, SUM(revenue) AS total_revenue FROM sales GROUP BY customer_id ORDER BY total_revenue DESC LIMIT 10;"

2. How would you handle missing data in a dataset?

This question evaluates your data cleaning and preprocessing skills.

How to Answer

Discuss various strategies for handling missing data, such as imputation, removal, or using algorithms that support missing values.

Example

"I would first analyze the extent of missing data. If it's minimal, I might remove those records. For larger gaps, I would consider imputation methods, such as using the mean or median for numerical data, or the mode for categorical data. Additionally, I would explore using algorithms that can handle missing values directly."

3. Can you explain the difference between a left join and an inner join?

This question tests your understanding of SQL joins.

How to Answer

Define both types of joins and explain their differences with examples.

Example

"A left join returns all records from the left table and matched records from the right table, while an inner join returns only the records that have matching values in both tables. For example, if we have a customers table and an orders table, a left join would show all customers, including those without orders, whereas an inner join would only show customers who have placed orders."

4. How do you optimize a slow-running SQL query?

This question assesses your ability to troubleshoot and improve query performance.

How to Answer

Discuss techniques such as indexing, query rewriting, and analyzing execution plans.

Example

"I would start by analyzing the query execution plan to identify bottlenecks. Then, I would consider adding indexes on columns used in WHERE clauses or JOIN conditions. Additionally, I would rewrite the query to eliminate unnecessary subqueries or joins, which can significantly improve performance."

5. Describe a Python project you worked on that involved data manipulation.

This question evaluates your practical experience with Python in data engineering.

How to Answer

Provide a specific example, detailing the project, the libraries used, and the outcome.

Example

"I worked on a project where I used Pandas to clean and analyze a large dataset of customer transactions. I implemented data transformations, such as merging datasets and creating new features, which helped the marketing team identify trends and improve targeting strategies."

Behavioral and Communication Skills

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

This question assesses your time management and prioritization skills.

How to Answer

Discuss your approach to prioritizing tasks based on urgency, impact, and stakeholder needs.

Example

"I prioritize tasks by assessing their urgency and impact on the overall project goals. I use tools like Trello to organize my tasks and regularly communicate with stakeholders to ensure alignment on priorities. This helps me manage my time effectively and deliver results on schedule."

2. Describe a time when you had to explain a complex technical concept to a non-technical audience.

This question evaluates your communication skills.

How to Answer

Provide an example of how you simplified a complex topic for a non-technical audience.

Example

"I once had to explain the concept of data pipelines to a marketing team. I used analogies, comparing the pipeline to a water system, where data flows from one point to another. I also created visual aids to illustrate the process, which helped them understand how data impacts their campaigns."

3. How do you handle feedback and criticism?

This question assesses your ability to accept and learn from feedback.

How to Answer

Discuss your approach to receiving feedback and how you use it for personal and professional growth.

Example

"I view feedback as an opportunity for growth. When I receive criticism, I take time to reflect on it and identify actionable steps for improvement. I appreciate constructive feedback and often seek it out to enhance my skills and performance."

4. Can you give an example of a successful collaboration with a cross-functional team?

This question evaluates your teamwork and collaboration skills.

How to Answer

Provide a specific example of a project where you collaborated with different teams and the outcome.

Example

"I collaborated with the product and engineering teams to develop a new reporting feature. I facilitated meetings to gather requirements and ensure everyone was aligned. By maintaining open communication and addressing concerns promptly, we successfully launched the feature on time, which improved user engagement."

5. Why do you want to work at Figma?

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

How to Answer

Discuss your interest in Figma's mission, values, and how your skills align with the role.

Example

"I admire Figma's commitment to making design accessible and collaborative. I believe my experience in building scalable data pipelines aligns well with your goals. I'm excited about the opportunity to contribute to a company that values innovation and teamwork."