LeetCode Question · Jan 2021 · Delhi

Delhivery | SDE 1

Data Eng Phone Screen Easy
13 upvotes 1,984 views 2 replies

Question Details

Round 1 Introduction and short discussion on my current work and product. DS / ALGO 1. Top View of a Binary Tree (Code) 2. Check if given Tree is BST or...

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Round 1 Introduction and short discussion on my current work and product.
DS / ALGO
1. Top View of a Binary Tree (Code)
2. Check if given Tree is BST or not (Code) - multiple approaches
3. Discussion on BST like data structure with duplicates
4. How HashMap internally works - explain worst case scenario in case of collisions
5. Discussion on BBSTs
* Need to explain the time and space complexties for all the solutions. Also time complexities of different operations in any DS which are being used in code.

OOPs / Java
1. Overloading vs Overriding
2. What if 2 functions in a class have same name and input paramaters but different return types. Will it work?
3. Runtime Polymorphism usecases with code
4. Inheritance related questions with code
5. Throw vs Throws
6. Finally block usage. Can it be used without try and catch. Can we put some code after try / catch but before finally block?
7. Generics in Java and it\'s advantage

Spring
1. What is the use of @SpringBootApplication annotation
2. Tell about @ComponentScan annotation in detail
3. How to configure multiple profiles (Dev, Test and Prod) in Spring Boot application
4. Discussion on application.properties file
5. What is @Bean annotation and what annotation we need to give at class level if we use it for any method
6. What is Spring Security and where did I use (no Syntax, just basic overview)

Kafka
1. What is Kafka
2. Advantages of using Kafka
3. How many consumers can read from a topic
4. Can a topic be written by multiple producers

Round 2 (Interviewer was the Team Lead of Platform team)

Detailed discussion on the work I do at my current org and discussion on the product I am working in.
Interviewer was more interested to know the impact I have made there.

  1. What DBs have you used. Explain the challenges faced with those DBs.
  2. Discussion on SQL blockages and ISOLATION levels
  3. SQL --> Given a person_details table with columns as id, name, gender, dob:
    a) Retrun all the person ids for all females having dob between 2000 to 2020
    b) How would you go about stroing additional information for address
    c) How would you make sure ZERO downtime on DB while introducing address details in db
    d) How would you store education details for a person
    e) Discussion on ways to optimize SQL queries. Advantages / Disadvantages of indexing
  4. How would you introduce Search functionality using SQL DBs. Can I use any other DB to achieve this ?
  5. How Elasticsearch works internally
  6. What things do I check while doing Code reivew
  7. What do you mean by RESTful web services
  8. What do you mean by Resources in REST
  9. Write REST endpoints for shopping cart functionlity (add/delete/update product or product quantities)
  10. Design an E-commerce shopping cart (LLD)
  11. How to make sure guest user doesn\'t lose cart items if he reloads the page
  12. Discussion on caching and in-memory dbs (Redis)
  13. How would you store Order transaction details
  14. How would you store Product details in db. Why did you choose NoSQL (Document based) db for this purpose.
  15. Generally, how would you take call which DB to use

Why do you want to join #Delhivery

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About This Question

This is a reported interview question from a elastic interview for a data eng role during the phone screen round reported in 2021.

It covers the following topics: Binary Tree, Hash Table, Sql, System Design .

Difficulty rating: Easy

About Elastic Interview Reports

This question was reported by a candidate who interviewed at Elastic. LeakCode aggregates interview reports from 10+ sources, including 1Point3Acres, Glassdoor, LeetCode Discuss, Blind, Reddit, Indeed, and Nowcoder. Each report is translated where necessary, deduplicated against existing entries, and tagged by company, role, round type, and reporting date.

Use this question as one calibration data point, not a memorization target. Companies typically rotate their question pools every 2-4 months; the exact wording of a 2024 question may differ from what you encounter today. The underlying pattern, difficulty level, and follow-up depth at Elastic are the higher-signal extractions to take from this report.

For broader preparation context, the Elastic interview process typically includes a recruiter screen, one or two technical phone screens, and a 4-5 round on-site loop covering coding, system design (at L4+ levels), and behavioral. Reports tagged on LeakCode show the round-by-round distribution and typical difficulty calibration. To browse questions filtered by round type and seniority, use the company hub linked above.

How To Practice This Type of Question

Solve similar problems on LeetCode under timed conditions (25-35 minutes per medium difficulty). The goal is pattern recognition: recognize the underlying technique (sliding window, two-pointer, BFS, memoized recursion, etc.) within 60-90 seconds of reading. Strong candidates verbalize their hypothesis out loud before coding, then iterate based on feedback. Weak candidates dive into implementation immediately, lose time on the wrong approach, and run out of time for follow-ups.

Companies update their question pools every 2-4 months. The exact wording of any given question may have been retired by the time you interview. Focus your prep on the pattern, not the specific problem. The patterns that appear in Elastic reports consistently are the ones worth investing in; one-off niche problems are not.

During Your Elastic Round

Apply the standard interview round template: clarify requirements (2-3 minutes), state your approach out loud and confirm direction with the interviewer (3-5 minutes), code with narration (15-25 minutes), test with concrete examples including edge cases (5 minutes), discuss optimization or trade-offs if time permits (5 minutes). This template is universally accepted across FAANG and adjacent companies; deviating from it produces weaker interviewer feedback signal.

The single most predictive failure mode in Elastic reports tagged "no hire": not asking clarifying questions. Interviewers are explicitly trained to weight this. Strong candidates ask 3-5 clarifying questions even on problems that look obvious; weak candidates dive into code immediately. The clarifying-question check is often the first signal recorded in the interviewer's written notes.