preparing for a technical interview at amazon or google

In October last year, I was offered a job to move to Seattle and work at Amazon!


It was an incredible opportunity. Amazon are giants, have interesting problems of scale to solve, and the chance to work in the US would be fantastic. Unfortunately, personal circumstances weren’t quite suitable for a move to the states at that time, and I had to decline. However, I really valued the experience and the chance to learn more about Amazon.

The offer meant that I felt brave enough to try for a job at Google in Sydney later that year. I didn’t do as well in that process, but the study techniques for both were the same.

There was a lot of work and preparation that went into the interviews – easily 60 to 80 hours. Here is a list of resources I found useful.

Cracking the Coding Interview by Gayle Laackman
This is an excellent book, and I would highly recommend this as the first port of call if you are short on time. For each category of problem (e.g. binary trees, bit arithmetic, logic, graphs, etc) there is a summary, hints and tips to look out for when answering the questions, sample questions and sample answers. I didn’t find anywhere else that collated this in one place.

This book will save you a lot of time and effort on research, and the sample questions are great to try as a warm up.   Most of my study time was spent attempting the questions in this book and trying to work out better/more efficient solutions. I would answer the first few questions without a time limit, and then try the next few with a 15 minute time limit – which is a realistic interview scenario.

Studying the performance/memory/space restrictions when answering the questions will probably make you stand out from the crowd.

Interactive Python course
Problem solving with data structures and algorithms does an excellent job of distilling complex topics into something really clear that you can follow.  It’s the right level of density and simplicity, with clear examples and descriptions of each data structure and algorithm, much better than the wikipedia versions.  I often came back to this site for reference. The sample code is in Python, but still very easily digested as someone who doesn’t know the syntax.

YouTube Videos
I had varying success looking at YouTube for some technical interviews (some were incredibly s-l-o-w, some were hard to understand) but I found a great series by Dickson Tsai, a tutor at UC Berkeley, called Data Structures in 5 minutes. The videos were good at concisely explaining a topic, although I often had to pause them to catch up. They alerted me to the existence of some concept that I might not have known before, e.g. the concept of a strongly connected graph. The main drawback is that the videos aren’t shot very professionally, but they do convey a lot of information in a short amount of time. Like speed studying. He also has a series of photos that go with the videos, because the board can be difficult to read at times.

There are also an amazing series of videos by AlgoRhythmics, which uses Hungarian folk dancing to show the efficiency of various search algorithms. I highly recommend them: as well as clearly highlighting the differences between algorithms, they are seriously awesome. I would like to buy a beer for the person who a) thought up the idea, and b) convinced an entire dance troupe to perform them.

Tips and tricks from current Googlers
Steve Yegge’s  Get That Job at Google and Cate Huston’s interviewing @ Google cover A LOT of different topics that you might encounter in a technical interview. It’s pretty much the same list that I was given by my Amazon and Google recruiters for study topics. It’s huge, and overwhelming. You won’t be able to cover it all in-depth, but nobody else will either.

Big-O Cheat Sheet
A list of all of the algorithm and data structure Big-O complexities in a single page.  It includes best, average and worst case time and space complexity and links to the relevant wikipedia articles.  Good to have handy if you’re having a phone interview!

Glassdoor is a good source of information about your potential employer, and the kinds of questions that might get asked in the interviews – just take the reviews with a grain of salt. If you trawl through the reviews and interview question examples, you will get a good idea about the kind of topics they cover, and possibly how difficult the questions might be.

Other things I found useful

  • Whiteboard & Whiteboard markers – I bought a cheap whiteboard and some thin whiteboard markers to practice solving problems, as you’ll have to do whiteboard coding in your interview.
  • Take photos of your solutions as you solve them, so you can review what you’ve done
  • Have a topic checklist. It helps you clarify what you need to study (you will be adding new topics to that list daily), AND you’ll feel great every time you tick something off that list.
  • Start a language topic translator if applicable – in my case, C# to Java. As you try to solve each problem, if you need to look up any language syntax just jot it down in a centralised place you can reference later.

Both Amazon and Google also provided an extensive list of material to review prior to interview. It included videos of what to expect on the day, hints and tips for what your interviewers will be looking for, and expected topics. Some of this material was private/password protected, so I don’t feel like I can share it here, but your recruiter will definitely provide a lot of information for you to review.

Good luck! 🙂 Feel free to ping me personally if you would like any more detail about my experiences with either Amazon or Google.

lambda ladies

I’m really excited to be able to attend Lambda Ladies in Brisbane, March 17-19.  It’s a free 3 day workshop run by Red Hat, using Haskell to cover a (re)introduction to functional programming. The last time I looked at functional programming after university was probably when F# came out.

I’m looking forward to a chunk of time looking at functional programming from a professional’s point of view, and not as a confused first year uni student!