Why Do FAANG Interviews Rely on LeetCode?
The rationale behind coding interviews and their role in selecting top engineering talent in Big Tech.
Last week, I wrote about mastering FAANG coding interviews in 57 days. The article was posted on Reddit, where someone commented:
The comment is valid, and I think many people feel the same way. The common argument is, "Why ask LeetCode problems if they won’t be directly useful in the actual job?" Put another way, “Why rely on theoretical knowledge to assess candidates for Software Development Engineer (SDE) roles?”
Initially, I was also in that group for arguing it, but I’ve come to understand the rationale behind these assessments. Let me explain my understanding of why LeetCode is necessary by starting with a reverse approach:
What skills are actually required for FAANG SDE positions?
Technical Skills
Programming Language: I think this is a fair skill, so there is nothing to add here.
Data structures and algorithms (DSA): In day-to-day life, SDEs write many lines of code and use different types of data structures to optimize the performance of systems by using the best suitable code for the requirements.
System design: This skill is a must-requirement if you're designing scalable and reliable systems.
Problem-solving and debugging: This is also a core skill in SDE's day-to-day life for identifying and resolving critical bugs in a production system.
Soft Skills
Effective communication: This is another must-have skill for any SDE.
Collaboration: All levels of SDEs need to collaborate with someone. It might include working with diverse teams, including engineers, product managers, and designers.
Adaptability: Many times, SDEs change teams, and employers, or work on different projects. So, transitioning to a new technology stack often requires learning new tools and techniques.
Attention to detail: This is another skill required to write high-quality code and deliverables by paying close attention to detail.
The importance of these skills varies by role and level, but top-performing SDEs excel in all these areas. I hope you’re agreeing until this moment.
Now, imagine you're running a company and need to hire a top-tier SDE. You posted the job opening and received 1,263 applications for a single position within 8 days. How would you assess all these candidates for the required skills?
The Challenge of Candidate Screening
You might already be thinking of matching the required skills to a candidate's experience through resume data. Through resume screening, you filtered many of the applications, leaving 264 applications. Obviously, your team does not have the capacity to assess 264 candidates by providing a real-world task or project, which takes weeks and months. No candidate wants to work on something for weeks that is not going to be used, perhaps with chances of getting rejected even after working on it. Right?
So you are working on creating a question that allows candidates to demonstrate their day-to-day skills within an hour so that candidates and employers can utilize their time to work for something more impactful.
This question will encourage candidates to:
Communicate effectively: Clearly articulate their understanding of the problem, clarify requirements, and propose solutions, allowing you to assess their communication and collaboration skills.
Think critically: Break down the problem into smaller subproblems, identify potential challenges and edge cases, and assess their problem-solving and attention to detail.
Demonstrate technical knowledge: Choose appropriate data structures and algorithms to implement an effective system, allowing you to assess their DSA skills.
Flexibility: Explore different approaches and adapt to changing requirements, allowing you to assess their adaptability and system design skills.
Write solution: Showcase their knowledge of day-to-day coding, allowing you to assess their programming skills.
Good Job for creating this question. This question allows both candidates and employers to save time while providing a fair assessment of skills relevant to the job.
To return to the original question: “Why rely on theoretical knowledge to assess candidates for SDE roles?” The answer is that coding interviews are not purely theoretical. They allow the interviewer to assess a wide range of practical, day-to-day skills required for SDE roles. I guess LeetCode questions started with this idea but over time it got lost/changed and many interviewers simply focused on DSA skills, which are not only required in top-tier SDE.
Bottom line: It’s the interviewer's responsibility to frame questions that simulate real-world scenarios so that the interview promotes collaboration and meaningful problem-solving where a candidate can showcase their day-to-day SDE skills.
The Future of SDE Interviews
Having said that, I believe the format of SDE interviews is likely to evolve (it should), especially with advancements in AI. For example, programming skills assessments may become less central to the process as AI tools make coding more accessible.
Hope this article provided clarity on the purpose of coding interviews. If you have any questions or thoughts, feel free to reply to this email or comment in this article so we all can learn from you!
I agree that DSA interviews are not solely about evaluating knowledge of data structures and algorithms. They also assess how candidates approach problems and communicate during the interview. This format is handy for evaluating entry-level candidates who may not have practical experience in areas like APIs or web development, as DSA concepts are commonly covered in computer science courses.
Additionally, I believe it's important to adopt a pragmatic approach: while some may disagree with being evaluated on DSA skills, it's often more beneficial to accept this as part of the process. Interview processes will never be perfect or completely fair, but instead of complaining, focusing on preparation and adapting to the rules of the game can lead to better outcomes. This mindset helps candidates navigate the interview landscape more effectively.