How to Prepare Yourself For Data Structures and Algorithms Interviews at FAANG

How to Prepare Yourself For Data Structures and Algorithms Interviews at FAANG

In this tutorial, I will how to prepare myself for data structures and algorithms interviews at FAANG

This was me in 2015 ☠️. A startup I had joined as “founding employee” after we raised a $500k seed round from a prototype was shut down six months later and we were looking for new roles. I secured an interview with Codecademy through a referral from one of the startup founders (also GIPHY but I wasn’t interested for some reason. Since then they sold to Facebook 🤦)

On the phone with Codecademy they said “don’t worry we don’t ask crazy algorithms questions or anything like that”. I took that to mean I didn’t need to study algorithms at all 🤣.

During the on-site interview, I got two rounds of algorithms questions that were extremely basic in hindsight. I remember one of them was asking how to traverse from point A to point B in a grid. I had no clue how to do that so I was just doing random shit. I landed on an infinite while loop… I actually wrote on the board:

In the loop, the point changed direction on each iteration depending on if it hit a wall and would eventually manually break the while loop if the target was found. The interviewer must’ve been like WTFFF, but he kept his cool and kept entertaining my different ideas.

That fiasco opened my eyes to the types of questions I needed to be able to answer. Two and a half months later I passed phone screens at Google, Uber, Shutterstock and Rent the Runway. I did the on-site interviews for Shutterstock, Rent the runway, and Uber and passed all of them. Google rescheduled my interview to be two weeks later than what I told them in the last minute. By that time I already had three offers and was pretty excited about Uber so I pulled the trigger and joined Uber.

I went from 0 → 100 in just a few months and I didn’t do anything special aside from studying consistently. That’s why I strongly believe any engineer can get good at these DS & Algo questions and get into F.A.A.N.G. or similar high paying roles.

At first, I felt I wasn’t really qualified because I had to study so hard to pass my interviews. In 2019, after having run my own consulting firm and startup for almost 2 years, I decided to go back into full-time work and found myself in the same position as I was in 2015.

This time, I had a larger network of friends at Uber and other top companies like Google and Facebook that gave me insight into the real deal. They all had to study just as hard. Even the ones that didn’t drop out of college like I did.

The ones who stayed and completed their Algorithms’ courses and had gotten their Computer Science degrees, they all still needed to study hard.

I discarded this notion of the mythical engineer who can on a whim pass a tech interview and started to appreciate the reality of the situation, that tech interviews are like the SAT’s they give in school. It doesn’t matter that you spent four years learning all of the content in high school, you still need to prep if you want to ace the test.

Just like with the SATs all of your past work and grades don’t contribute to the score. Your success depends entirely on how well you perform on the test.

Once I realized the truth, that everybody needs to study, it was enough motivation for me to put in the hard work since I realized that’s what my competition was doing. Through that motivation, I formed a process for studying that helped me pass every tech screen and on-site interview I did in 2019. I, a college dropout, passed technical screens for Stripe, Coinbase and Triplebyte. I passed screens and on-site interviews for Google, Amazon, Uber (again), Reddit, Squarespace and Braze.

A 100% pass rate wasn’t expected and isn’t likely to continue to happen, but I believe focusing on the fundamentals helps approach that goal.

data-structures algorithms interview-prep

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