Electronic Arts (EA) Data Engineer Interview Questions + Guide in 2024

Electronic Arts (EA) is a titan in the interactive entertainment industry. Established in 1982, EA has become one of the world’s largest video game companies, renowned for its popular game franchises such as FIFA, Madden NFL, The Sims, and Battlefield. With a commitment to creativity and cutting-edge technology, EA continues to lead in producing interactive entertainment that enthralls millions globally.

Stepping into a Data Engineer role at EA requires a blend of technical prowess and creativity. This position involves managing and optimizing data pipelines, ensuring data quality and integrity, and supporting the analytical needs of the company. Typical interview stages may include phone screenings, coding tests, technical interviews, and behavioral assessments, with a strong focus on problem-solving, theory, and performance engineering.

If you aim to join the team, our guide will help you navigate the interview process, from common Electronic Arts data engineer interview questions to tips for success. Get ready to embark on a journey with one of the most exciting companies in the gaming industry. Let’s dive in!

The interview process usually depends on the role and seniority; however, you can expect the following on an Electronic Arts data engineer interview:

Recruiter/Hiring Manager Call Screening

If your application makes it through the initial screening, you will likely receive a call from a recruiter at EA. This initial interview generally lasts around 30 minutes. During this call, the recruiter will verify your background, interest in the role, and if you’re interviewing with other companies. Expect questions such as:

• Tell me about yourself
• Why do you want to work here?
• What’s your favorite project?
• Are you currently interviewing with other companies?

This is an excellent opportunity to ask any preliminary questions you have about the company or the role.

Technical Virtual Interview

If you pass the initial screening, you’ll be invited to a technical interview. The focus here may include theories rather than just practical examples. It may delve into performance engineering, programming methods (functional, OO, etc.), and your ability to write code under timed conditions.

For instance, you might be asked:

• Explain the difference between different programming methods (functional, OO, etc.).
• What is a vtable, and what is its purpose?
• Write a program that takes a list of strings and substitutes the characters based on some required patterns.

Questions may also cover specific programming languages like C++, statistics, machine learning, and your favorite project lifecycle stage.

Onsite Interview Rounds

After succeeding in the technical virtual interview, you may proceed to onsite interview rounds, varying in length and complexity. Typically, these would include:

• Panel interviews with team members and higher management focusing on behavioral and situational questions.
• A deep dive into your technical skills and project experiences.
• Detailed discussions on data management, work ethics, and possibly a coding challenge in JavaScript or another relevant language. Additional stakeholder interviews may cover game industry experience, project management, and team dynamics.

Example questions can include:

• Tell me about yourself.
• What’s your management style?
• How do you deal with increasing scope and difficult stakeholders?

These interviews evaluate your technical proficiency and cultural fit within the company.

Following these guidelines will help you navigate the interview process at EA and present yourself as a standout candidate.

Typically, interviews at Electronic Arts vary by role and team, but common data engineer interviews follow a fairly standardized process across these question topics.

1. Write a function to simulate coin tosses based on the number of tosses and probability of heads.

Create a function that takes the number of tosses and the probability of heads as inputs. The function should return a list of randomly generated results, where ‘H’ represents heads and ’T’ represents tails. The length of the list should be equal to the number of tosses.

2. What is the formula for calculating the average lifetime value for a SAAS company?

You work for a SAAS company with a product costing $100/month, a 10% monthly churn rate, and an average customer lifespan of 3.5 months. Calculate the formula for the average lifetime value.

3. What metrics/graphs/models would you use to analyze churn behavior for different Netflix pricing plans?

Netflix has two pricing plans: $15/month or $100/year. An executive wants to analyze the churn behavior of users subscribing to either plan. What metrics, graphs, or models would you build to provide an overarching view of subscription performance?

4. How would you analyze cross-platform user experience for web and mobile?

You need to analyze user interaction data on both web and mobile to optimize cross-platform user experience. The database includes two tables: one for mobile actions and one for web actions. Determine the number of unique users visiting only mobile pages and the percentage of web-only visitors, and write a query to return the percentage of users visiting only mobile, only web, and both.

5. How would you select and test a pre-launch of a new show on Amazon Prime Video?

Amazon Prime Video wants to pre-launch a new show to 10,000 customers. How would you select the best 10,000 customers for the pre-launch, and what would the process look like to measure the show’s performance?

6. What would happen to the conversion rate after applying a new UI to all users?

You tested a new UI to increase conversion rates, and the test variant won by 5% on the target metric. After applying the new UI to all users, will the metric actually go up by ~5%, more, or less? Assume there is no novelty effect.

7. How would you evaluate the performance of a decision tree model before and after deployment?

If you decide to use a decision tree model, how would you assess its performance before deployment and monitor it after deployment?

8. What is the concept of LDA in machine learning and its use cases?

Explain the concept of Linear Discriminant Analysis (LDA) in machine learning. What are some practical use cases for LDA?

9. How would you collect and aggregate unstructured video data for an ETL pipeline?

You are designing an ETL pipeline for a model that inputs videos. How would you collect and aggregate unstructured data from videos?

10. How would you create a system to detect firearm listings on a marketplace?

You are designing a marketplace where selling firearms is prohibited. How would you create a system to detect if a listing is selling a gun automatically?

11. How would you design a YouTube video recommendation system?

You are tasked with building the YouTube video recommendation algorithm. How would you design the recommendation system, and what important factors should you consider?

Example 1:

Input:

tosses = 5
probability_of_heads = 0.6

Output:

coin_toss(tosses, probability_of_heads) -> ['H', 'T', 'H', 'H', 'T']

Example 2:

Input:

tosses = 3
probability_of_heads = 0.2

Output:

coin_toss(tosses, probability_of_heads) -> ['T', 'T', 'T']

The output may vary due to the randomness of coin tosses.

To excel in EA interviews, consider the following tips based on previous candidate experiences:

1. Be Prepared but Relaxed: EA interviews can be a positive and stress-free experience if you prepare well. Familiarize yourself with EA’s core values and be ready to discuss how your experiences align with them.

2. Showcase Gaming Knowledge: Expect questions related to gaming and specific technical skills relevant to the gaming industry. Demonstrate your passion for gaming and any related experience you have.

3. Maintain Professional Follow-Up: While EA’s staff is generally responsive, the process can sometimes take a while. Maintain professional communication and follow up thoughtfully if there are delays.

What is the average salary for a Data Engineer at Electronic Arts (Ea)?

What is the company culture like at EA?

EA’s company culture is known to be friendly and respectful, emphasizing collaboration and continuous improvement. The interviewers and recruiters are generally supportive and transparent, which helps create a positive and stress-free experience for candidates. However, experiences can vary, and keeping an open mind is always good.

What should I do if I don’t hear back after an interview?

If you don’t hear back after an interview, it’s advisable to follow up with your recruiter or point of contact at EA. While the communication is generally good, there can be delays. Persistence in following up shows your interest in the position, but always remain professional and courteous in your communication.

As a trailblazer in the gaming industry, Electronic Arts (EA) is always looking for talented and innovative data engineers to join its dynamic team.

Dive deep into preparation, showcase your adaptability and problem-solving skills, and you’ll position yourself as a standout candidate. If you’re passionate about gaming and data and are ready to join a world-class team, EA could be the next great step in your career journey.

Best of luck with your interview at Electronic Arts, and may your efforts lead you to an exciting and fulfilling role!