How Google Interviews in 2026: Process, Questions & What They Score

1. 01

   Given an encoded string, return its decoded string (string parsing/stack problem)

   Stack-based string parsing; nested multipliers make an explicit stack or recursion the expected approach.

2. 02

   Design and implement an LRU Cache (one of the most consistently cited Google coding questions across multiple sources)

   Classic data-structure design: hash map plus doubly linked list for O(1) get and put.

3. 03

   Number of Islands: count connected components in a grid (frequently reported across all levels)

   Grid connected-components problem; flood fill with DFS/BFS and visited-state bookkeeping.

4. 04

   Word Ladder: find the shortest transformation sequence between two words using a dictionary (graph/BFS problem)

   Shortest-path search over word transformations; model words as graph nodes and BFS level by level.

5. 05

   Merge Intervals: merge overlapping intervals in a list

   Sort-then-sweep technique: order intervals by start and merge overlaps in one pass.

6. 06

   Implement a SnapshotArray supporting versioned get/set operations

   Versioned data-structure design: per-index history with binary search over snapshot ids.

7. 07

   Two Sum / variants and Longest Substring Without Repeating Characters (common warm-up/phone-screen level questions)

   Warm-up staples: hash map complement lookup and sliding window over characters.

8. 08

   Various tree/graph traversal, dynamic programming, and trie problems, especially at senior levels (L5+) where interviewers reportedly favor tries, graphs, and DP over simpler array problems

   Senior-level pattern round: tries, graphs, and DP favored at L5+ over simple array problems.

Reported problems, listed so you know what to expect. Practice them in your own editor or on the platform you prefer; SupaCV's practice mode coaches how you talk through them.

1. 01

   Design a URL-shortening service (e.g., TinyURL/goo.gl)

   System design staple: ID generation and encoding, redirect latency, and read-heavy caching.

2. 02

   Design a rate limiter (cited as one of the most universally asked system design questions across FAANG, including Google)

   System design: token bucket versus sliding window algorithms and distributed counter state.

3. 03

   Design a webpage/system to display real-time status for 10M+ users (name, photo, badge, points), a specifically Google-reported question

   System design: fan-out and caching for 10M+ users, freshness versus load trade-offs.

4. 04

   Design a job/task scheduler that assigns jobs to machines with constrained CPU/RAM, also specifically documented as a Google interview question

   Resource-aware scheduling: bin packing jobs onto machines under CPU/RAM constraints with queuing and retries.

5. 05

   Design a recommendation system for a content platform (e.g., YouTube-style video recommendations)

   System design with ML flavor: candidate generation, ranking, and feedback loops for content recommendations.

6. 06

   Design a scalable, high-throughput backend for a Google-scale product (search-adjacent, ads-adjacent, or infrastructure-flavored prompts are common given Google's product surface)

   Tests capacity estimation, partitioning, replication, and latency budgets at Google scale.

Reported problems, listed so you know what to expect. Practice them in your own editor or on the platform you prefer; SupaCV's practice mode coaches how you talk through them.

1. 01

   Open-ended hypothetical prompts, e.g., 'X country has a high advertiser churn rate. As Country Marketing Manager, how would you solve it?' (a documented, specifically-reported Google GCA question)

2. 02

   'You're expected to organize an offsite for your team. How would you go about planning it?' (documented Google hypothetical/GCA-style question)

3. 03

   Fermi/estimation questions: 'How many tennis balls fit into a typical car?'

4. 04

   Fermi/estimation: 'Estimate the number of videos watched on YouTube per day'

5. 05

   Fermi/estimation: 'How much revenue does the Play Store generate per year?'

6. 06

   Fermi/estimation: 'What is the market size for driverless/self-driving cars?' (a specifically documented Google PM/GCA-style estimation question)

1. 01

   What is your favorite product and why? How would you improve it?

1. 01

   Imagine you launch a new feature, and the day after launch usage drops dramatically. How do you investigate the incident?

1. 01

   How many messages per second does Gmail receive?

1. 01

   Tell me about a time you faced a challenge or conflict with a colleague or stakeholder

2. 02

   Tell me about a time you had to come up with a creative solution to a problem

3. 03

   Tell me about a time you created something from nothing (0-to-1 ownership)

4. 04

   Tell me about a time you failed or made a mistake: what did you learn?

5. 05

   Tell me about a time you had to deal with significant ambiguity

6. 06

   Tell me about a time you disagreed with a decision or pushed back on the status quo

7. 07

   Describe a time you had to influence or lead a team without formal authority

8. 08

   Describe a time you received difficult feedback and how you responded

1. 01

   Follow-up probing on a past project: how you defined assumptions, structured the problem, and adapted as new information emerged