Zomato SDE - 1 | 2022 grad | 9 months experience | Gurgaon | onsite| accepted

I learned about the opportunity through a friend's referral and LinkedIn posts. Zomato primarily considers referred applications, and after applying multiple times, I finally received an interview call one week post-referral. Interestingly, there was no initial coding round.

I was invited for an onsite interview at Zomato's office.

Round 1

This round began with a discussion of my experience and projects at Synopsys. The interviewers were very relaxed and created a comfortable atmosphere, even conversing in 'hinglish'. After detailing my work, we moved into a low-level design problem. I was asked to consider 1 million objects, each with 3-4 properties, and determine the optimal data structure to store them, focusing on fast retrieval of record groups. We discussed the factors influencing data structure choice and how a query would retrieve data from my proposed structure.

Next, I was tasked with writing code to parse a JSON file and transform its nested structure into a flattened key-value format (e.g., a: {a1: 123, a2: {b: "abc"}} to a.a1 = 123, a.a2.b = "abc"). Following this, they presented a classic DSA problem: finding the longest substring with an equal number of 0s and 1s in a binary string. I solved this efficiently within 5 minutes and then thoroughly tested it with their provided test cases. The interviewers seemed quite satisfied, and I was shortlisted for the next round.

Round 2

This round also started with introductions and questions about my work at Synopsys. The first major problem was a system design challenge: how to distribute incoming application requests across multiple servers to ensure an almost equal load, essentially designing a load balancer. I proposed token bucket and leaky bucket approaches, then elaborated on consistent hashing, explaining its differences from normal hashing and outlining each step involved. We also discussed primary and secondary indexing.

Subsequently, they asked me to detail the entire lifecycle of a request, covering DNS, caching, and gateways. We explored the internal workings of a gateway, Content Delivery Networks (CDNs) and their types, and how DNS resolution leads to a server response. We also discussed various factors to reduce latency, such as vertical and horizontal scaling and geo-DNS routing.

Finally, I was asked to design a basic music player system, similar to Spotify, incorporating features like creating playlists, adding songs, and searching. I needed to specify the appropriate database, explain normalization and denormalization strategies for optimizing queries, and propose a suitable schema. The interviewers were pleased with my responses and provided feedback immediately. About 30 minutes later, I received confirmation that I had cleared the second round, and we proceeded to discuss compensation.