Angel One | SDE 2 | Backend | Onsite | Rejected
Interview Experience
There were 2 questions in the PS round: Q1: https://leetcode.com/problems/largest-submatrix-with-rearrangements/ I was able to think about the prefix height at every row but was confused about how to maximize by rearranging. However,...
Full Details
There were 2 questions in the PS round:
Q1: https://leetcode.com/problems/largest-submatrix-with-rearrangements/
I was able to think about the prefix height at every row but was confused about how to maximize by rearranging. However, with some help, I was able to complete it. After the interview, I checked my code/logic, and it was perfect.
Time taken: 30 min
Q2: https://leetcode.com/problems/minimum-consecutive-cards-to-pick-up/description/
I solved this in 2 minutes using hashmaps, and the interviewer was shocked. He even tried some edge cases, but it worked flawlessly. After the interview, I checked my code again, and it was still flawless.
Time taken: 5 min
The interview literally ended 10 minutes early, but 15 minutes later, I got an automated response that I was
rejected. So, if I get stuck and ask for a hint, it means straight rejection. I called HR and asked for feedback to which she read the interviewer\'s words "the candidate was not able to complete the solution even after multiple hints? gap in knowledge for problem solving" lol nice
So if i have such shallow understanding why tf was Mr. prefect was shocked when i wrote the 2 sol under 5 mins
The Indian tech industry is doomed. All those who have jobs are lucky, but trust karma\u2014these stupid DSA-memorizing Indian devs will meet their fate later.
He asked me what tech stacks and technologies i am proficient with that discussion went for 5 mins
frameworks : nestjs, nodejs, django, springboot.
db : mysql, postgres, mongodb (exploring cassandra and vitess.io)
timeseries optmised : mongo ts, timescale, influx
search optmised : elastic (open search), algolia(fully managed service)
About This Question
This is a candidate experience report from a elastic interview for a backend role during the onsite round reported in 2024.
It covers the following topics: Hash Table .
Topics
About Elastic Interview Reports
This question was reported by a candidate who interviewed at Elastic. LeakCode aggregates interview reports from 10+ sources, including 1Point3Acres, Glassdoor, LeetCode Discuss, Blind, Reddit, Indeed, and Nowcoder. Each report is translated where necessary, deduplicated against existing entries, and tagged by company, role, round type, and reporting date.
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For broader preparation context, the Elastic interview process typically includes a recruiter screen, one or two technical phone screens, and a 4-5 round on-site loop covering coding, system design (at L4+ levels), and behavioral. Reports tagged on LeakCode show the round-by-round distribution and typical difficulty calibration. To browse questions filtered by round type and seniority, use the company hub linked above.
How To Practice This Type of Question
Solve similar problems on LeetCode under timed conditions (25-35 minutes per medium difficulty). The goal is pattern recognition: recognize the underlying technique (sliding window, two-pointer, BFS, memoized recursion, etc.) within 60-90 seconds of reading. Strong candidates verbalize their hypothesis out loud before coding, then iterate based on feedback. Weak candidates dive into implementation immediately, lose time on the wrong approach, and run out of time for follow-ups.
Companies update their question pools every 2-4 months. The exact wording of any given question may have been retired by the time you interview. Focus your prep on the pattern, not the specific problem. The patterns that appear in Elastic reports consistently are the ones worth investing in; one-off niche problems are not.
During Your Elastic Round
Apply the standard interview round template: clarify requirements (2-3 minutes), state your approach out loud and confirm direction with the interviewer (3-5 minutes), code with narration (15-25 minutes), test with concrete examples including edge cases (5 minutes), discuss optimization or trade-offs if time permits (5 minutes). This template is universally accepted across FAANG and adjacent companies; deviating from it produces weaker interviewer feedback signal.
The single most predictive failure mode in Elastic reports tagged "no hire": not asking clarifying questions. Interviewers are explicitly trained to weight this. Strong candidates ask 3-5 clarifying questions even on problems that look obvious; weak candidates dive into code immediately. The clarifying-question check is often the first signal recorded in the interviewer's written notes.