Fastly Data Engineer Interview Questions + Guide in 2025

Fastly is at the forefront of modern internet infrastructure, providing an edge cloud platform that allows businesses to create exceptional digital experiences by processing, serving, and securing applications close to their end-users.

As a Data Engineer at Fastly, you will play a pivotal role in building and maintaining the data infrastructure that supports data-driven decision-making across the organization. Your key responsibilities will include designing and implementing data pipelines, managing data transformations, and ensuring data quality and accessibility. You will collaborate closely with cross-functional teams, including analytics and product teams, to identify key performance indicators (KPIs) and develop robust data products that empower the business to make informed decisions.

To excel in this role, you should possess strong SQL skills and be comfortable working with cloud data warehouse technologies. Experience with data visualization tools and familiarity with data governance practices are also essential. A detail-oriented mindset, along with the ability to communicate technical concepts to non-technical stakeholders, will set you apart. Fastly values collaboration, creativity, and integrity, and as such, a great fit would be someone who embodies these values while being passionate about leveraging data to solve complex business challenges.

This guide will help you prepare effectively for your interview by providing insights into the expectations, skills, and cultural fit that Fastly seeks in a Data Engineer.

The interview process for a Data Engineer role at Fastly is designed to assess both technical skills and cultural fit within the organization. It typically consists of several stages, each focusing on different aspects of the candidate's qualifications and alignment with Fastly's values.

1. Initial Recruiter Screen

The process begins with a phone interview with a recruiter, which usually lasts about 30 minutes. During this conversation, the recruiter will discuss the role, the company culture, and the candidate's background. Expect to answer behavioral questions that help the recruiter gauge your fit for the team and the organization. This stage is also an opportunity for candidates to ask questions about the company and the role.

2. Technical Screening

Following the initial screen, candidates typically undergo a technical interview. This may be conducted via video call and focuses on assessing the candidate's technical skills relevant to data engineering. Expect questions related to SQL, data modeling, and possibly coding challenges that reflect real-world scenarios you might encounter in the role. The technical interviewer may also explore your experience with data transformation tools and cloud data warehouse technologies.

3. Behavioral and Values Interview

Candidates will then participate in a behavioral interview, which may involve multiple interviewers. This stage assesses how well candidates align with Fastly's core values. Questions may revolve around past experiences that demonstrate your ability to collaborate, prioritize tasks, and manage relationships with stakeholders. Be prepared to discuss specific examples that highlight your problem-solving skills and how you embody the company's values.

4. Peer Interviews

Next, candidates may have interviews with potential peers or team members. These discussions often focus on team dynamics and collaboration. Interviewers will likely ask about your experience working in cross-functional teams and how you handle challenges in a collaborative environment. This stage is crucial for assessing how well you would integrate into the existing team.

5. Final Interview with Hiring Manager

The final stage typically involves a one-on-one interview with the hiring manager. This conversation will delve deeper into your technical expertise and how you can contribute to the team's goals. Expect to discuss your approach to data engineering challenges, your understanding of the business metrics that drive performance, and how you would prioritize projects. This is also an opportunity for you to ask more in-depth questions about the team's objectives and expectations.

As you prepare for your interviews, consider the specific skills and experiences that will resonate with the interviewers, particularly in areas like SQL proficiency and data analytics. Next, let's explore the types of questions you might encounter during this process.

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

Embrace the Interview Process

Fastly's interview process is known for being thorough and multi-faceted, often involving several rounds that assess both technical skills and cultural fit. Approach each stage with enthusiasm and a willingness to engage. Remember, the interviewers are not just evaluating your skills; they are also assessing how well you align with the company's values and culture. Be prepared to discuss your experiences in detail and how they relate to Fastly's mission of building a more trustworthy Internet.

Showcase Your Technical Expertise

As a Data Engineer, your proficiency in SQL and algorithms will be crucial. Brush up on complex SQL queries and be ready to demonstrate your problem-solving skills through coding challenges. Familiarize yourself with data transformation tools and cloud data warehouse technologies, as these are essential for the role. Expect technical questions that require you to think critically and articulate your thought process clearly. Practice explaining your technical decisions and the rationale behind them, as this will showcase your analytical thinking.

Prepare for Behavioral Questions

Fastly places a strong emphasis on cultural fit, so be ready to answer behavioral questions that explore your values and how they align with the company’s. Reflect on past experiences where you demonstrated qualities such as collaboration, integrity, and transparency. Use the STAR (Situation, Task, Action, Result) method to structure your responses, ensuring you convey not just what you did, but also the impact of your actions.

Communicate Effectively

Throughout the interview, clear communication is key. Be concise yet thorough in your answers, and don’t hesitate to ask clarifying questions if you need more context. Fastly values transparency, so be honest about your experiences and what you can bring to the team. Additionally, prepare thoughtful questions to ask your interviewers about the team dynamics, ongoing projects, and how success is measured within the role.

Demonstrate Your Passion for Data

Fastly is looking for candidates who are not only skilled but also passionate about data and its potential to drive business decisions. Share examples of how you have used data to solve complex problems or improve processes in your previous roles. Highlight any projects where you took the initiative to create data products or dashboards that empowered stakeholders to make informed decisions.

Be Adaptable and Open-Minded

Given the dynamic nature of Fastly's work environment, showcasing your adaptability will be beneficial. Be prepared to discuss how you handle change and uncertainty, as well as your approach to learning new technologies or methodologies. This will demonstrate your readiness to thrive in a fast-paced, evolving landscape.

Follow Up Thoughtfully

After your interviews, consider sending a follow-up email to express your gratitude for the opportunity and reiterate your interest in the role. This not only shows professionalism but also reinforces your enthusiasm for joining Fastly. If you have any additional thoughts or questions that arose after the interview, feel free to include them in your follow-up.

By preparing thoroughly and embodying the values that Fastly stands for, you will 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 Fastly. The interview process will likely assess your technical skills, problem-solving abilities, and cultural fit within the company. Be prepared to discuss your experience with data transformation, SQL, and analytics, as well as your approach to collaboration and communication with stakeholders.

Technical Skills

**1. Explain how you would design a data pipeline for a new product feature.

This question assesses your understanding of data architecture and your ability to translate business needs into technical solutions.**

How to Answer

Discuss the steps you would take to gather requirements, design the pipeline, and ensure data quality and reliability. Highlight any tools or technologies you would use.

Example

“I would start by collaborating with product managers to understand the specific data needs for the new feature. Then, I would design a data pipeline using tools like Apache Airflow for orchestration and dbt for transformations, ensuring that data is clean and accessible for analysis. Finally, I would implement monitoring to catch any issues early.”

**2. How do you optimize SQL queries for performance?

This question evaluates your SQL expertise and understanding of database performance.**

How to Answer

Explain the techniques you use to optimize queries, such as indexing, query restructuring, or analyzing execution plans.

Example

“To optimize SQL queries, I first analyze the execution plan to identify bottlenecks. I often use indexing on columns that are frequently filtered or joined. Additionally, I rewrite complex queries to reduce the number of joins and subqueries, which can significantly improve performance.”

**3. Describe a challenging data transformation you have implemented.

This question looks for your problem-solving skills and experience with data transformations.**

How to Answer

Share a specific example, detailing the challenge, your approach, and the outcome.

Example

“In a previous role, I needed to transform raw sales data into a format suitable for analysis. The challenge was dealing with inconsistent data formats. I implemented a series of dbt models to standardize the data, which improved our reporting accuracy and reduced the time spent on data cleaning by 30%.”

**4. What strategies do you use to ensure data quality and integrity?

This question assesses your understanding of data governance and quality assurance.**

How to Answer

Discuss the processes you implement to maintain data quality, such as validation checks, automated testing, and documentation.

Example

“I implement data validation checks at various stages of the data pipeline to catch errors early. Additionally, I document data sources and transformations to ensure transparency and facilitate audits. Regularly scheduled data quality reviews with stakeholders also help maintain integrity.”

**5. How would you handle a situation where stakeholders have conflicting data requirements?

This question evaluates your communication and negotiation skills.**

How to Answer

Explain your approach to understanding stakeholder needs and finding a compromise or solution.

Example

“I would first meet with each stakeholder to understand their specific requirements and the reasoning behind them. Then, I would facilitate a discussion to identify common goals and propose a solution that meets the most critical needs while ensuring data consistency.”

Behavioral Questions

**1. Describe a time when you had to work with a difficult team member.

This question assesses your interpersonal skills and ability to navigate team dynamics.**

How to Answer

Share a specific example, focusing on how you handled the situation and what you learned.

Example

“I once worked with a team member who was resistant to feedback. I approached them privately to discuss our project goals and how their contributions fit into the bigger picture. By fostering open communication, we were able to align our efforts and improve collaboration.”

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

This question evaluates your time management and organizational skills.**

How to Answer

Discuss your approach to prioritization, including any tools or methods you use.

Example

“I use a combination of project management tools and prioritization frameworks like the Eisenhower Matrix to manage my tasks. I assess the urgency and importance of each task and communicate with stakeholders to ensure alignment on priorities.”

**3. Can you give an example of how you contributed to a data-driven decision?

This question looks for your ability to leverage data for business impact.**

How to Answer

Provide a specific example where your analysis influenced a decision.

Example

“In my last role, I analyzed customer behavior data to identify trends in product usage. My findings led to a strategic decision to enhance certain features, resulting in a 20% increase in user engagement over the next quarter.”

**4. How do you stay current with industry trends and technologies?

This question assesses your commitment to professional development.**

How to Answer

Share the resources you use to keep your skills up to date, such as online courses, blogs, or conferences.

Example

“I regularly follow industry blogs and participate in online forums related to data engineering. I also attend webinars and conferences to learn about new technologies and best practices, ensuring that I stay informed about the latest trends.”

**5. What company values resonate with you the most, and why?

This question evaluates your cultural fit and alignment with Fastly’s values.**

How to Answer

Reflect on the company’s values and share which ones resonate with you and why.

Example

“I resonate with Fastly’s commitment to transparency and collaboration. I believe that open communication fosters trust and leads to better outcomes, both in team dynamics and in delivering value to customers.”