System Design

Ace Your System Design Mock Interview at Epic Games

By: Chris Garzon | February 9, 2025 | 4 mins read

Preparing for a system design mock interview can be daunting, especially for a company as prestigious as Epic Games. In this blog post, we will break down key insights from a mock interview conducted, focusing on how to effectively approach system design questions and technical challenges.

Understanding the Basics of System Design

What is System Design?

System design is the process of defining the architecture, components, modules, interfaces, and data for a system to satisfy specified requirements. It involves understanding how different parts of a system interact with each other and how data flows through the system.

Why is it Important?

In a tech-driven environment like Epic Games, system design skills are crucial for building scalable, efficient, and robust applications. Mastering these concepts can set you apart in interviews and help you excel in your role.

Key Elements of the Mock Interview

The Initial Scenario

During the mock interview, the candidate was presented with a real-world question that required designing a system to manage sales data for video games across different platforms. The interviewer emphasized the importance of understanding the requirements and constraints before diving into the solution.

Breaking Down the Problem

The candidate was tasked with creating a table to represent sales data, where each row would indicate a sale, including details like the title and platform of the game. This initial step laid the groundwork for a more complex system design.

Designing the System

Choosing the Right Tools

The discussion quickly moved to the tools needed to build the system. The candidate suggested using an API caller to format data in JSON, which is essential for handling live data. The interviewer prompted the candidate to think critically about the architecture, leading to a conversation about using AWS services like Lambda, Kinesis, and Redshift.

Data Flow and Transformation

The candidate proposed a flow where data is captured via an API, processed through a Lambda function, and then sent to Kinesis Firehose. However, the interviewer guided the candidate to consider additional steps, such as storing data in S3 before transforming it for Redshift. This iterative approach is vital in system design.

Data Modeling Considerations

Historical Data Storage

A significant part of the discussion revolved around how to store historical data. The candidate was asked whether to use a single table or multiple tables for different types of data. This question highlighted the importance of data modeling in system design.

Partitioning Data

The candidate suggested partitioning data into different datasets, such as hourly or daily partitions. The interviewer emphasized the need for a balance between granularity and performance, leading to a discussion on the trade-offs of hourly versus daily data storage.

Best Practices for System Design Interviews

Ask Clarifying Questions

When faced with vague questions, it’s essential to ask clarifying questions to understand the requirements better. This approach not only demonstrates your analytical skills but also helps avoid miscommunication.

Think Aloud

During the interview, verbalizing your thought process can be beneficial. It allows the interviewer to follow your reasoning and provides opportunities for feedback and guidance.

Consider Scalability

Always keep scalability in mind when designing systems. Discuss how your design can handle increased loads and how it can be adapted for future needs.

Conclusion

Acing a system design mock interview at Epic Games requires a solid understanding of system architecture, data modeling, and the ability to communicate your thought process effectively. By following the insights shared in this mock interview with Christopher Garzon, you can enhance your preparation and increase your chances of success. Remember, practice makes perfect, so keep refining your skills and approach. Good luck!

Unlock Your Career Potential

Upskill and start shaping your future with DEAcademy today.

Frequently asked questions

Haven’t found what you’re looking for? Contact us at [email protected] — we’re here to help.

What is the Data Engineering Academy?

Data Engineering Academy is created by FAANG data engineers with decades of experience in hiring, managing, and training data engineers at FAANG companies. We know that it can be overwhelming to follow advice from reddit, google, or online certificates, so we’ve condensed everything that you need to learn data engineering while ALSO studying for the DE interview.

What is the curriculum like?

We understand technology is always changing, so learning the fundamentals is the way to go. You will have many interview questions in SQL, Python Algo and Python Dataframes (Pandas). From there, you will also have real life Data modeling and System Design questions. Finally, you will have real world AWS projects where you will get exposure to 30+ tools that are relevant to today’s industry. See here for further details on curriculum  

How is DE Academy different from other courses?

DE Academy is not a traditional course, but rather emphasizes practical, hands-on learning experiences. The curriculum of DE Academy is developed in collaboration with industry experts and professionals. We know how to start your data engineering journey while ALSO studying for the job interview. We know it’s best to learn from real world projects that take weeks to complete instead of spending years with masters, certificates, etc.

Do you offer any 1-1 help?

Yes, we provide personal guidance, resume review, negotiation help and much more to go along with your data engineering training to get you to your next goal. If interested, reach out to [email protected]

Does Data Engineering Academy offer certification upon completion?

Yes! But only for our private clients and not for the digital package as our certificate holds value when companies see it on your resume.

What is the best way to learn data engineering?

The best way is to learn from the best data engineering courses while also studying for the data engineer interview.

Is it hard to become a data engineer?

Any transition in life has its challenges, but taking a data engineer online course is easier with the proper guidance from our FAANG coaches.

What are the job prospects for data engineers?

The data engineer job role is growing rapidly, as can be seen by google trends, with an entry level data engineer earning well over the 6-figure mark.

What are some common data engineer interview questions?

SQL and data modeling are the most common, but learning how to ace the SQL portion of the data engineer interview is just as important as learning SQL itself.