Google

My interview process for the Google Software Engineering Intern role started with an online coding assessment. The OA had two coding problems, and I found both of them significantly more difficult than the usual internship assessments I had practiced. The problems required me to think about the constraints carefully and identify the right data structure or algorithm rather than immediately trying to code a brute-force solution. I was able to solve one problem completely and make substantial progress on the other. The test cases were hidden, so I could not rely on seeing whether my code was passing while taking the assessment. This made it especially important to reason about edge cases before submitting. A selected candidate reported a similar two-question OA with hard problems and described them as roughly in the 1800–2000 Codeforces range. After clearing the assessment, I had two technical interviews. The first one started with a short introduction and then moved directly into a DSA problem involving a priority queue. I was able to identify the approach fairly quickly and implement it during the discussion. Once I had the basic solution working, the interviewer introduced a follow-up and asked me to modify the approach accordingly. I explained the reasoning behind my solution instead of simply jumping into the implementation, and I also discussed its time and space complexity. The second interview was based around graph traversal. I was given a problem where DFS/BFS was the key idea, and I was able to solve it without needing significant hints. Compared with the first round, there were fewer follow-ups, but I still had to explain why the traversal worked and how the complexity would change for different constraints. Other reported Google internship interviews similarly emphasize DSA, optimization, complexity analysis, and communicating the thought process rather than merely producing code. One thing I noticed throughout the interviews was that the interviewer was interested in how I arrived at the solution. I made sure to explain the brute-force idea first when appropriate, point out its limitations, and then move toward the optimized approach. I also tried to keep the implementation straightforward and discussed edge cases before finishing. After completing the technical rounds, I received the selection update. Overall, the process was heavily focused on DSA and problem solving, with the interviews testing how well I could reason through unfamiliar problems under time pressure. Based on my experience, preparation for Google should include not only solving difficult problems but also practicing how to communicate the solution clearly while coding.