Atlassian | Interview Experience | P40 | 5 YOE | Awaiting Team Match
Summary
I shared my detailed Atlassian interview experience for a SWE-II P40 backend role, covering multiple rounds including Karat screening, LLD, DSA, System Design, and Management & Values. I received positive feedback for all rounds and am currently awaiting team match.
Full Experience
I'm sharing my detailed Atlassian interview experience for SWE-II P40 backend role.
I'll share the questions if I remember for those rounds, but most of the questions were from interview experiences I found on leetcode.
Before I start, please avoid asking these unnecessary informations
- My current company
- My current compensation
- Offered compensation ( as it is not discussed yet )
So, I reached out to multiple recruiters through mail or linkedin message requests, on which one of the recruiter replied after 20 days and scheduled screening round. Overall from the day recruiter reached out till today almost 2 months are passed, and today I called recruiter and got to know that HC has approved my profile and will assign another recruiter that will drive team matching process.
Round 1: Karat Screening Round (1 Hour)
It was an hour long round which was mostly divided into two parts. First part was 20 mins rapid fire round where he asked some system design scenarios and I've to suggest possible solutions with justification. And second part was having 2 DSA questions mostly easy-medium difficulty level.
After 3 days recruiter informed that screening was cleared and started main Atlassian interview rounds
Round 2: LLD (1 Hour)
It was an LLD round and similar question that mentioned as here. Overall round was medium and interviewer was friendly and communicating properly.
Round 3: DSA (1 Hour)
I was asked question similar to merge interval problem just with different wording and few follow ups that required sweep line approaches. Overall round was easy for me as I've huge practise in DSA and interviewer was friendly and communicating properly.
4 days after these two rounds, I called recruiter and was informed that feedback was positive and can move to system design round.
Round 4: System Design (1 Hour)
It was a Top-k heavy hitter problems for confluence page with a variation that user should no be shown the pages in top k which he has already viewed. You can search Top-k heavy hitter on internet you'll find lots of variation of it. Overall round was good, few small mistakes I did but recruiter was supportive and he fully focused the interview on areas what he needs to see and clarify assumptions beforehand so that I don't waste time on those.
1 hour after the interview, recruiter informed about positive feedback and can move to MV rounds
Round 5 & 6: Management and Values (1 hour each)
Both of the rounds were similar. I was asked some situations and based on my previous work experience I've to justify those situations basically in STAR format. Only difference is that questions in values round were more aligned toward Atlassian values.
After 3 days, I was informed that both rounds were also positive and waiting for HC approval. Since it was a year end time so it took almost a month.
Final Verdicts:
LLD - Hire, High Confidence
DSA - Hire, High Confidence
HLD - Hire, Medium Confidence
Management - Hire
Values - Hire
Will update once team matching will progress.
Hope for the best!!!
Interview Questions (2)
I was asked a question similar to the merge interval problem, but with different wording. It also included follow-up questions that required sweep line approaches.
The system design problem involved finding the Top-k heavy hitter problems for a Confluence page. A specific variation was that users should not be shown pages in the top-k that they have already viewed. I discussed the design, and the interviewer was supportive, guiding me to clarify assumptions and focus on critical aspects, even with minor mistakes.
Preparation Tips
I primarily prepared by practicing a vast number of Data Structures and Algorithms problems. I found many useful questions by exploring other interview experiences shared on LeetCode.