GoPro is a leading technology company renowned for its innovative cameras and action sports gear, dedicated to enabling people to capture and share their most exciting experiences.

As a Software Engineer at GoPro, you will play a crucial role in the Data Science Engineering (DSE) team, focusing on the design, development, and implementation of scalable data solutions within a big data ecosystem. Your key responsibilities will include understanding business requirements, collaborating with various teams to develop data models, and creating reliable data pipelines that serve multiple business units such as marketing and product engineering. You will be expected to lead the design and operation of data platforms, ensuring they meet high standards of quality and performance. Strong programming skills in Scala or Java, along with proficiency in big data tools such as Spark, Hive, and AWS cloud services, are essential for success in this role. Additionally, a passion for problem-solving and a meticulous attention to detail will help you navigate complex datasets and deliver actionable insights.

This guide will equip you with the necessary knowledge and insights to excel in your interview with GoPro, helping you effectively showcase your technical skills and alignment with the company's values.

The interview process for a Software Engineer role at GoPro is designed to assess both technical skills and cultural fit within the company. Candidates can expect a structured approach that includes multiple rounds of interviews, focusing on their ability to work with big data technologies and software engineering best practices.

1. Initial Screening

The process begins with an initial screening, typically conducted by a recruiter. This 30-minute phone interview focuses on understanding the candidate's background, skills, and motivations for applying to GoPro. The recruiter will also provide insights into the company culture and the specifics of the Software Engineer role, ensuring that candidates have a clear understanding of what to expect.

2. Technical Assessment

Following the initial screening, candidates will undergo a technical assessment, which may be conducted via a coding platform or through a live coding session. This round focuses on evaluating the candidate's proficiency in programming languages such as Scala or Java, as well as their understanding of algorithms and data structures. Candidates should be prepared to solve problems related to data pipeline design, data modeling, and querying databases using SQL.

3. Behavioral Interview

The next step in the process is a behavioral interview, where candidates will meet with a hiring manager or team lead. This interview aims to assess the candidate's soft skills, such as communication, teamwork, and problem-solving abilities. Candidates should be ready to discuss past experiences, how they handle challenges, and their approach to collaboration with both technical and non-technical peers.

4. Onsite Interview (or Virtual Equivalent)

The final stage of the interview process is an onsite interview, which may be conducted virtually. This round typically consists of multiple one-on-one interviews with team members and stakeholders. Candidates will be evaluated on their technical expertise, ability to design scalable data solutions, and their fit within the team. Expect discussions around big data technologies, cloud services, and the candidate's approach to operational excellence in software engineering.

Throughout the interview process, candidates should be prepared to demonstrate their technical knowledge and problem-solving skills, as well as their ability to synthesize business requirements into technical solutions.

Next, let's explore the specific interview questions that candidates have encountered during this process.

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

Understand the Big Data Ecosystem

Familiarize yourself with the components of the Big Data technology stack, including data modeling, data lakehouses, data pipelines, and data analytics. Be prepared to discuss how you have utilized tools like Hive, Spark, Databricks, Presto, Kafka, or Airflow in your previous projects. Demonstrating a solid understanding of these technologies will show your readiness to contribute to GoPro's data initiatives.

Showcase Your Software Development Skills

Proficiency in Scala or Java is crucial for this role. Brush up on your coding skills and be ready to discuss your experience in designing and developing scalable data solutions. Prepare to share specific examples of how you have implemented best practices in software engineering, particularly in the context of data engineering.

Prepare for Problem-Solving Scenarios

Expect to encounter questions that assess your problem-solving abilities. GoPro values meticulous attention to detail and the capacity to tackle loosely defined problems. Practice articulating your thought process when faced with complex challenges, and be ready to provide examples of how you have successfully navigated similar situations in the past.

Communicate Effectively

Strong interpersonal skills are essential for collaborating with both technical and non-technical peers. Practice explaining technical concepts in a clear and concise manner. Be prepared to discuss how you have worked with cross-functional teams to gather business requirements and translate them into technical specifications.

Embrace GoPro's Culture of Autonomy

GoPro emphasizes autonomy and trust in its employees. During the interview, express your appreciation for a work environment that encourages independence and innovation. Share examples of how you have taken initiative in previous roles and how you thrive in a flexible work setting.

Highlight Your Passion for Data

Demonstrate your enthusiasm for data and analytics. Discuss any personal projects or experiences that showcase your interest in data-driven decision-making. This will resonate with GoPro's mission to empower teams through data and analytics.

Be Ready to Discuss Cloud Services

Experience with AWS or other cloud services is a plus for this role. Familiarize yourself with the cloud technologies you have used and be prepared to discuss how you have leveraged them to build scalable and reliable data solutions. Highlight any experience you have with MLOps, as this knowledge can set you apart from other candidates.

Prepare Questions for Your Interviewers

Engage your interviewers by preparing thoughtful questions about the team, projects, and company culture. This not only shows your interest in the role but also helps you assess if GoPro is the right fit for you. Consider asking about the challenges the team is currently facing or how they measure success in their data initiatives.

By following these tips, you will be well-prepared to showcase your skills and align with GoPro's values during your interview. Good luck!

GoPro Software Engineer Interview Questions

In this section, we’ll review the various interview questions that might be asked during a GoPro software engineering interview. The interview will focus on your technical skills, particularly in software development, big data technologies, and problem-solving abilities. Be prepared to discuss your experience with data pipelines, data modeling, and cloud services, as well as your approach to collaborating with cross-functional teams.

Technical Skills

1. Can you explain the architecture of a big data technology stack and its components?

Understanding the architecture of big data systems is crucial for this role, as it involves working with various technologies to build scalable solutions.

How to Answer

Discuss the layers of the big data stack, including data ingestion, storage, processing, and analytics. Highlight your experience with specific technologies and how they fit into this architecture.

Example

“The big data technology stack typically consists of layers such as data ingestion tools like Kafka, storage solutions like HDFS or cloud storage, processing frameworks like Spark, and analytics tools for visualization. In my previous role, I designed a data pipeline using Kafka for ingestion, Spark for processing, and Tableau for visualization, which allowed us to derive insights from large datasets efficiently.”

2. Describe your experience with designing and building data pipelines. What tools have you used?

This question assesses your hands-on experience with data engineering and the tools you are familiar with.

How to Answer

Mention specific tools and frameworks you have used, such as Apache Spark, Airflow, or Databricks, and describe a project where you implemented a data pipeline.

Example

“I have extensive experience designing data pipelines using Apache Spark and Airflow. In my last project, I built a pipeline that ingested data from various sources, processed it in real-time using Spark, and stored it in a data lake for further analysis. This setup improved our data processing speed by 40%.”

3. How do you ensure the quality and reliability of the datasets you work with?

Quality assurance is vital in data engineering, and this question evaluates your approach to maintaining data integrity.

How to Answer

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

Example

“To ensure data quality, I implement automated testing at various stages of the data pipeline. I also use data profiling techniques to identify anomalies and set up monitoring alerts for any discrepancies. This proactive approach has helped us maintain a high level of data integrity in our projects.”

4. Can you explain your experience with SQL and how you optimize queries for performance?

SQL proficiency is essential for this role, and interviewers will want to know how you handle database interactions.

How to Answer

Talk about your experience with SQL, including specific optimizations you have implemented to improve query performance.

Example

“I have worked extensively with SQL to create and optimize queries for large datasets. I focus on using indexed columns, avoiding SELECT *, and leveraging window functions to enhance performance. In one instance, I optimized a complex query that reduced execution time from several minutes to under 30 seconds.”

5. What is your experience with cloud services, particularly AWS?

As cloud services are integral to modern data solutions, this question assesses your familiarity with cloud platforms.

How to Answer

Discuss specific AWS services you have used, such as S3, EC2, or Redshift, and how they were applied in your projects.

Example

“I have utilized AWS services extensively, particularly S3 for data storage and EC2 for running data processing jobs. In a recent project, I set up an ETL process using AWS Glue to extract data from S3, transform it using Lambda functions, and load it into Redshift for analytics, which streamlined our data workflow significantly.”

Problem-Solving and Collaboration

1. Describe a challenging problem you faced in a project and how you resolved it.

This question evaluates your problem-solving skills and ability to navigate complex situations.

How to Answer

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

Example

“In a previous project, we faced significant latency issues with our data pipeline. I conducted a thorough analysis and discovered that the bottleneck was in the data transformation stage. I re-architected the pipeline to parallelize the processing tasks, which reduced latency by 60% and improved overall system performance.”

2. How do you approach collaboration with non-technical stakeholders?

Collaboration is key in a cross-functional environment, and this question assesses your communication skills.

How to Answer

Discuss your approach to understanding business requirements and translating them into technical solutions.

Example

“I prioritize clear communication and active listening when working with non-technical stakeholders. I often use visual aids to explain complex concepts and ensure that I fully understand their needs. This collaborative approach has led to successful project outcomes and stronger relationships with business teams.”

3. Can you give an example of how you have mentored or supported junior engineers?

This question assesses your leadership and mentoring abilities, which are important in a team environment.

How to Answer

Share a specific instance where you provided guidance or support to junior team members.

Example

“I took on a mentoring role for a junior engineer who was struggling with data modeling concepts. I organized weekly sessions to review best practices and worked on a project together, which helped them gain confidence and improve their skills. Seeing their progress was incredibly rewarding.”

4. How do you stay updated with the latest technologies and trends in data engineering?

This question evaluates your commitment to continuous learning and professional development.

How to Answer

Discuss the resources you use to stay informed, such as online courses, webinars, or industry publications.

Example

“I regularly follow industry blogs, participate in webinars, and take online courses to stay updated on the latest trends in data engineering. I also attend local meetups and conferences to network with other professionals and share knowledge, which helps me stay at the forefront of technology advancements.”

5. What strategies do you use to manage your time and prioritize tasks in a fast-paced environment?

Time management is crucial in a dynamic work setting, and this question assesses your organizational skills.

How to Answer

Share your approach to prioritizing tasks and managing deadlines effectively.

Example

“I use a combination of task management tools and agile methodologies to prioritize my work. I break down larger projects into smaller, manageable tasks and set clear deadlines. This approach allows me to stay focused and adapt quickly to changing priorities while ensuring that I meet project goals.”

• Write a query to get the average order value by gender. Given three tables representing customer transactions and customer attributes, write a query to get the average order value by gender. Round the answer to two decimal places.

• Write a function missing_number to find the missing number in an array. You have an array of integers, nums of length n spanning 0 to n with one missing. Write a function missing_number that returns the missing number in the array. Complexity of (O(n)) required.

• Find the index where the sum of the left half equals the right half in a list. Given a list of integers, find the index at which the sum of the left half of the list is equal to the right half. If there is no such index, return -1.

• Write a function sorting to sort a list of strings in ascending order. Given a list of strings, write a function sorting from scratch to sort the list in ascending alphabetical order. Do not use the built-in sorted function. Return the new sorted list.

• Write a query to find the earliest date each user played their third unique song. Given a table of song_plays and a table of users, write a query to extract the earliest date each user played their third unique song. If a user has listened to less than three unique songs, display their name with a NULL date and song name.

• How would you build a model to predict which merchants DoorDash should acquire in a new market? As a data scientist at DoorDash, describe the steps and features you would use to build a predictive model to identify which merchants the company should target for acquisition when entering a new market.

• How would you determine the customer service quality through the chat box for small businesses on Facebook Marketplace? Working at Facebook, your team aims to help small businesses increase sales through the Marketplace app. Explain how you would assess the quality of customer service provided through chat interactions between small businesses and consumers.

• What business health metrics would you track on a dashboard for an e-commerce D2C sock business? If you are in charge of an e-commerce D2C business selling socks, list and explain the key business health metrics you would monitor on a company dashboard to ensure the business's success.

• Write a query to determine if user interactions (likes, comments) lead to higher purchasing volumes. Given three tables (users, transactions, and events), write a SQL query to analyze whether users who interact on the website (e.g., likes, comments) have a higher purchasing volume compared to those who do not interact.

• How does random forest generate the forest and why use it over logistic regression? Explain the process of generating a forest in a random forest algorithm and discuss the advantages of using random forest over logistic regression.

• How do we deal with missing square footage data to construct a housing price model? You have 100K sold listings over the past three years for Seattle, but 20% are missing square footage data. Describe methods to handle the missing data to build an accurate housing price prediction model.

• How would you build a model to predict which merchants DoorDash should acquire in a new market? As a data scientist at DoorDash, outline the steps to create a model that predicts which merchants the company should target for acquisition when entering a new market.

• How do you detect and handle correlation between variables in linear regression? Describe methods to detect and manage correlation between variables in a linear regression model. Explain the consequences of ignoring such correlations in the model.

• How would you design a model to detect potential bombs at a border crossing? Outline the design of a model to detect potential bombs at a border crossing, including the selection of inputs and outputs, methods to measure accuracy, and strategies to test the model.

• How many more samples are needed to decrease the margin of error from 3 to 0.3? Given a sample size (n) with a margin of error of 3, calculate the additional samples required to reduce the margin of error to 0.3.

• What is the mean and variance of the distribution of (2X - Y)? Given (X) and (Y) are independent random variables with normal distributions (X \sim \mathcal{N}(3, 4)) and (Y \sim \mathcal{N}(1, 4)), determine the mean and variance of (2X - Y).

• How do you calculate the sample size and power for an AB test? For an AB test with a test group and a control group:

• Explain how to calculate the necessary sample size for accurate measurement.
• If the sample size is sufficient, should the power increase or decrease to measure very small differences between the groups?

Considering a software engineering position at GoPro offers an exciting opportunity to be at the forefront of big data technology, supporting a variety of business needs within its innovative ecosystem. The roles emphasize a balanced approach to autonomy and collaboration, leveraging cutting-edge technologies and promoting a flexible work environment.

If you want more insights about the company, check out our main GoPro Interview Guide, where we have covered many interview questions that could be asked. We've also created interview guides for other roles, such as software engineer and data analyst, where you can learn more about GoPro’s interview process for different positions.

At Interview Query, we empower you to unlock your interview prowess with a comprehensive toolkit, equipping you with the knowledge, confidence, and strategic guidance to conquer every GoPro software engineering interview question and challenge.

You can check out all our company interview guides for better preparation, and if you have any questions, don’t hesitate to reach out to us.

Good luck with your interview!