Atlassian | P40 | India [Offer]

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SE-25 yearsOffer
August 12, 202516 reads

Summary

Secured a P40 role at Atlassian in India after a rigorous interview process spanning multiple days. The interview included system design, coding, code design, managerial, and values interviews. The candidate had a strong background with 5 years of experience, including 3 years at a FAANG company, which significantly contributed to their success.

Full Experience

Applied to multiple SDE2 openings and received a call from a recruiter, marking the start of the interview process. The journey began with a Karat interview on Day 1, which focused on system design questions. The candidate tackled challenges related to implementing a friend-count feature for a Facebook clone, discussing scalability for a rapidly growing platform. They also addressed a load balancing issue in a Google Docs clone, evaluating consistency models for various applications, and solving a bug tracking scenario involving missing IDs.

Day 6 brought a Data Structures interview where the candidate was asked to determine the minimum latency between services in a network, leading to a discussion on Dijkstra's algorithm and its advantages over DFS and BFS. On Day 7, a Code Design interview focused on building a customer satisfaction system, with the candidate following Test-Driven Development (TDD) principles as advised by the recruiter.

Day 13 featured another System Design interview for a Tagging Management Service, emphasizing product-agnostic design and technologies like SQS, RabbitMQ, and Kafka. The candidate received feedback on the design's completeness. The Managerial Interview on Day 16 was standard, while the Values Interview on Day 20 aligned with LeetCode-discussed questions. The process concluded with a team matching call and ultimately, an offer was accepted.

Interview Questions (7)

Q1
Friend Count Feature Implementation
System Design

Implement a feature to display the number of friends a post's author has at the time of viewing the post for a Facebook clone. The database schema includes USER and USER RELATIONSHIP tables. The solution must scale for a rapidly growing platform.

Q2
Load Balancing in Google Docs Clone
System Design

Assess the implications of a round-robin load balancing system for a Google Docs clone where each document is handled by a single server. Evaluate potential scalability issues and suggest solutions.

Q3
Consistency Models for Applications
System Design

Determine whether strong or eventual consistency is more appropriate for the following applications:
- An API call to retrieve video stream metadata within 20 milliseconds.
- A web analytics platform recording every click on a popular web page.
- A banking system handling deposits and payments.

Q4
Missing IDs in Log Files
System Design

Identify the IDs that were missing from a database when there was a bug causing failed requests. You have access to a database storing all IDs and large log files from 500 production servers logging successful request IDs.

Q5
Minimum Latency Between Services
Data Structures & AlgorithmsHard

Given a network of N services with connection latencies, determine the minimum latency from service X to service Y for Q queries. Discuss why classic DFS and BFS are not suitable, how Dijkstra's algorithm would work, and explore alternative solutions and their time complexities.

Q6
Customer Satisfaction System
Code Design

Design a customer support ticketing system that allows customers to rate agents and provides average ratings for each agent, ordered from highest to lowest. Extend the system to track the best agents each month.

Q7
Tagging Management Service
System Design

Design a product-agnostic tagging system for Atlassian's products (Jira, Confluence, Bitbucket) that allows users to tag, view, and manage content by tags. Include features for adding/removing tags, viewing content by tags, and displaying popular tags.

Preparation Tips

Prepared by leveraging previous FAANG experience, focusing on system design, coding, and TDD practices as recommended by recruiters. Reviewed consistency models and scalability strategies. Engaged in multiple interviews, including managerial and values interviews, to align with Atlassian's culture and expectations.

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