SDE 2 @ Kotak
Summary
I interviewed for an SDE 2 position at Kotak, which involved multiple rounds covering DSA, LLD, and HLD, but I was ultimately rejected due to perceived gaps in my LLD design.
Full Experience
Round 1
- DSA: https://leetcode.com/problems/container-with-most-water/description/
- LLD: Design an e-commerce platform order, tracking and delivery system. Handle multiple items with various quantities in a single order, partial and full cancellation support.
- HLD: Given we have an e-commerce platform, how would you handle processing very high amounts of data for analytics and preparing relevant dashboards? Which database you may consider?
Round 2
- Few questions on some tech stack I worked on
- LRU cache implementation
Round 3
- LLD + HLD of a limit system in Kotak. This should limit based on number of transactions, amount per user’s payment method. Handle atomicity, possible bottlenecks etc.
Verdict
Rejected. The panel found few gaps in LLD in #3 :(
Interview Questions (5)
Given n non-negative integers a1, a2, ..., an such that each represents a point at coordinate (i, ai). n vertical lines are drawn such that the two endpoints of line i are (i, ai) and (i, 0). Find two lines, which, together with the x-axis forms a container, such that the container contains the most water.
Design an e-commerce platform order, tracking and delivery system. Handle multiple items with various quantities in a single order, partial and full cancellation support.
Given we have an e-commerce platform, how would you handle processing very high amounts of data for analytics and preparing relevant dashboards? Which database you may consider?
Design and implement a data structure for a Least Recently Used (LRU) cache. It should support the following operations: get and put. get(key): Get the value (will always be positive) of the key if the key exists in the cache, otherwise return -1. put(key, value): Set or insert the value if the key is not already present. When the cache reaches its capacity, it should invalidate the least recently used item before inserting a new item.
Design an LLD + HLD of a limit system in Kotak. This should limit based on number of transactions, amount per user’s payment method. Handle atomicity, possible bottlenecks etc.