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GoogleΒ· SWE - II (L3)

πŸš€ Google Interview Experience (2 Rounds) SWE - II (L3)

Posted
8 May 2026
633 reads

Summary

Interview consisted of two rounds: a DSA round focusing on graphs and a behavioral round assessing past projects and problem-solving approaches.

How it went

I recently had the opportunity to interview with Google, and I wanted to share my experience.

Round 1: DSA (Graphs)

The round focused on a graph-based problem (easy–medium level).

Problem Summary:
Given a weighted graph and a node, remove that node along with all its connected edges, and return the maximum edge weight remaining in the graph.

I explored multiple solutions during the discussion:
Priority Queue Approach:
Stored all edges in a max-heap and kept popping until I found an edge not connected to the removed node.
Multiset Approach:
Used a sorted structure to maintain edges and efficiently retrieve the maximum valid edge.

Optimized Preprocessing Approach (Final Solution):
Built an auxiliary structure to precompute the maximum edge weight for each node after its removal.
This allowed answering queries in O(1) time.

πŸ’‘ The interviewer seemed reasonably satisfied, especially with the progression from brute-force to optimized thinking.

πŸ’¬ Round 2: Googliness (Behavioral Round)

This round focused on:

  • Past projects
  • Problem-solving approaches
  • Real-life situations
  • Ownership and decision-making

Overall, it was a great learning experience. The process really tests both technical depth and problem-solving mindset, along with how you approach real-world challenges.

Questions asked (1)

  1. 01

    Remove Node and Return Max Edge Weight

    Data Structures & Algorithms Β· Medium

    You're given a weighted graph and a specific node. Your task is to remove that node and all edges connected to it. After removal, return the maximum edge weight among the remaining edges in the graph.

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