Summary
I interviewed for an SDE 2 position at Booking Holdings in Bangalore and successfully received an offer despite a challenging culture fit round. The process included an OA/DSA round and a system design problem focused on hotel availability synchronization.
Full Experience
My interview journey for the SDE 2 role at Booking Holdings in Bangalore encompassed several rounds. The Online Assessment and Data Structures & Algorithms round was referenced as being similar to another experience shared on LeetCode. A key challenge was the System Design round, where I was tasked with designing a robust system to synchronize hotel availability across various platforms like Booking, Airbnb, Agoda, and Expedia, with the critical constraint of preventing overbookings. The Culture Fit round proved to be the most demanding. I felt intensely scrutinized, and it seemed the interviewers were looking for specific responses, often overlooking my actual project experiences. Explaining my project and convincing them of its successful problem resolution required four attempts. Despite feeling certain of rejection after this round, I was fortunate to receive an offer.
Interview Questions (1)
Design a system to sync availability of hotels which are listed across multiple sites like Booking, Airbnb, Agoda, Expedia etc. We need to ensure we do not book a hotel room when it's already sold out.
Preparation Tips
My preparation involved general LeetCode practice for the Data Structures & Algorithms round, given that it was referenced as being similar to another posted experience. For the System Design interview, my focus was on understanding and applying principles for designing scalable and reliable distributed systems, which directly helped in tackling the hotel availability synchronization problem. There was no specific mention of unique preparation for the Culture Fit round, but effective communication and detailed project explanations were crucial.
Summary
I interviewed for an SE-2 position at Booking Holdings (Booking.com) in Bangalore with 5 years of experience and received an offer after successfully completing an online assessment, DSA, system design, and hiring manager rounds.
Full Experience
My interview journey for the SE-2 role at Booking Holdings (Booking.com) in Bangalore was structured and thorough. With approximately 5 years of professional experience, I began with an online assessment, followed by three distinct onsite interview rounds.
Round 1: Online Assessment (2 hours)
This round was conducted via Hackerrank. I was tasked with creating a REST API using Spring Boot and then pushing the completed code to the master branch. This round assessed my practical coding and API development skills.
Round 2: Data Structures & Algorithms (1 hour)
I faced a problem that was a variation of the classic Sliding Window Maximum. It was presented as a story-based problem, which made it less straightforward than a typical LeetCode problem, requiring careful understanding of the narrative.
Round 3: System Design (1 hour)
This round focused on my system design capabilities. I was asked to propose a High-Level Design (HLD) for a Centralized Logging System.
Round 4: Hiring Manager (1 hour)
The final round involved discussions primarily centered on my past work experiences and behavioral questions, assessing my fit within the team and company culture.
Ultimately, I was selected and received an offer for the position.
Interview Questions (3)
I was tasked with creating a REST API using Spring Boot within a 2-hour timeframe and pushing the completed code to a master branch. This involved understanding requirements, implementing API endpoints, and handling version control effectively.
I was presented with a story-based problem that was a variation of the classic Sliding Window Maximum problem. The core concept involved finding the maximum element within a sliding window of a given size, but with additional context and constraints from the story, making it a non-trivial adaptation.
I had to design a Centralized Logging System at a high level. This involved discussing key components such as log producers, aggregators, robust storage solutions, efficient search capabilities, and how to ensure scalability for handling potentially massive volumes of log data.