Incubyte Data Engineer Interview Questions and Answers

Questions related to web development and quantitative aptitude. It was one hour test. Based on the score of this test, the position is allotted to you for which you are eligible to give the interview.

Coding round didn't had compilers and I had to write the pseudo code for the given problems. Few DSA and SQL questions were there in this round.

Q1. This round was with the CEO of the company. He asked me to introduce myself and later switch to technical questions. He gave me a problem based on nested-dictionary type of thing and also few SQL queries t...read more
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Mostly questions on logical aptitude

Q1. DSA questions. Reverse word of string, bubble sort, swap two variables without use of third variable
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Q2. OOPs concepts also some questions on project
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Q3. 1 puzzle (refer gfg)
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Q1. Why do you want to work at our company?
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Q2. What was the toughest challenge you have ever faced?
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Q1. Questions related to my tech stack
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Q1. Behavioral round with manager
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Q1. Questions related to my tech stack
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60 Minutes coding test was there

Q1. Worst experience ever, never apply for company in this, highly unstable company
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Q2. Add two numbers in a linked list, don't apply
Ans. 
Traverse the linked list and add the values of each node without using additional data structures.
• Traverse the linked list while keeping track of the sum in a variable

• Update the sum by adding the value of each node as you traverse the list

• Handle carry over if the sum of two nodes is greater than 9
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Q3. Sort the array by using all sorting algorithms, don't join
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Q4. Subset problem find all the subsets
Ans. 
To find all subsets of a given set, use recursion to generate all possible combinations.
• Use recursion to generate all possible combinations of including or excluding each element in the set.

• Start with an empty subset and recursively add each element to create new subsets.

• Each subset can be represented as an array of strings.
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Q5. LRU Cache problem, explain it and implement it
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LRU Cache is a data structure that stores a fixed number of items and removes the least recently used item when the cache is full.
• LRU Cache uses a combination of a doubly linked list and a hashmap to efficiently store and retrieve items.

• When an item is accessed, it is moved to the front of the linked list to indicate it is the most recently used item.

• If the cache is full, the least recently used item at the end of the ...read more
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