Bloomberg | Interview Experience | Senior Software Engineer - 4+ YOE | NYC | Nov 2025

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bloomberg
Senior Software EngineerNYC4 yearsNo Offer
November 14, 20257 reads

Summary

I interviewed for a Senior Software Engineer position at Bloomberg in November 2025, undergoing several technical rounds. Unfortunately, I did not receive an offer to proceed further, but I am sharing the problems I encountered to assist others in their preparation.

Full Experience

My interview process for the Senior Software Engineer role at Bloomberg consisted of multiple rounds. The first round, lasting 60 minutes, focused on an algorithmic problem. Following this, I had a second 90-minute round that presented two distinct coding challenges. Finally, I participated in a 90-minute system design round. Despite my efforts, I did not receive an offer.

Interview Questions (4)

Q1
Gas Station / Oasis / Car Path Problem
Data Structures & Algorithms

A problem often referred to as 'Gas Station', 'Oasis', or 'Car Path Problem'.

Q2
Insert Delete GetRandom O(1)
Data Structures & Algorithms

Design a lottery system that supports adding a participant, removing a participant, and getting a random participant, all in O(1) time complexity.

Q3
Sum of Two Integers with Restrictions
Data Structures & Algorithms

Similar to the 'Sum of Two Integers' problem but with additional restrictions. I was explicitly told not to use the addition operator, loops, or bitwise logic. The interviewer guided me to use recursion, modulo, and integer division.

Q4
Design a Web Application for Financial Information
System Design

Design a web application capable of supporting user onboarding, password reset, requesting company information, and IT help requests. The system requires independent deployments. It's critical to ensure all requests are authenticated and validated, especially since highly sensitive financial information is being handled. The discussion covered trade-offs between various technologies and concepts:

  • Databases (SQL vs. NoSQL, focusing on ACID and CAP theorems)
  • Load balancing
  • Caching strategies
  • Blue/green deployments
  • API gateways
  • Cloud vs. on-premise infrastructure
  • Considerations for reliability, scalability, and security
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