Google

Getting the Google interview call was honestly one of those moments where I immediately started overthinking my preparation. I had been doing DSA regularly, but once the interview was scheduled, every problem suddenly felt harder than usual. The process started with the coding round. I got two DSA questions. I managed to solve one completely, while the second one took much longer than expected. After that, I was shortlisted for the technical interviews. Public Google India reports also describe two technical rounds with one DSA problem and follow-ups in each. In the first technical round, the interviewer gave me a problem similar to **Merge Intervals**. My first approach was straightforward, and after explaining it, the interviewer asked what could be improved. I eventually got to the expected approach and coded it, but I made a silly mistake during the dry run and had to correct it. The interviewer was patient and kept asking questions instead of immediately giving hints. A similar India report describes a Merge Intervals-type problem with a follow-up. The second round was tougher. I was given a **tree/DFS-based problem**. I found a working approach fairly quickly, but it wasn't optimal. When the interviewer asked about the complexity, I realized I had missed an important observation. I tried improving it while explaining my thought process, but I couldn't reach the expected solution within the remaining time. Similar reports mention DFS/BFS and greedy problems where the optimal approach was the main challenge. A few days later, I got the rejection mail. It hurt, obviously, but the interviews were actually a good reality check. I realized that knowing DSA isn't enough at this level—I need to get much faster at identifying the optimal approach and communicating it clearly while coding.