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Complete Google L4 SDE-2 Interview Preparation Guide

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Pushkar Kathayat

Complete Google L4 SDE-2 Interview Preparation Guide

Interview Structure (4-5 Rounds)

Round Breakdown

  1. •Phone Screen: 45 min - 1-2 DSA problems
  2. •Onsite (4 rounds):
    • •2-3 Coding rounds: DSA problems (45 min each)
    • •1 Behavioral round: Googleyness & Leadership (45 min)
    • •0-1 System Design: Optional for L4 (depends on team/background)

Part 1: Data Structures & Algorithms (60% focus)

Core Data Structures

1. Arrays & Strings

Patterns:

  • •Two Pointers (O(N) vs O(N²))
  • •Sliding Window (fixed/variable size)
  • •Kadane's Algorithm (max subarray)

Key Problems:

  • •Container With Most Water
  • •Longest Substring Without Repeating Characters
  • •Trapping Rain Water
  • •Product of Array Except Self

2. Hash Tables

Patterns:

  • •Frequency counter
  • •Index mapping
  • •Complement search

Key Problems:

  • •Two Sum, Three Sum, Four Sum
  • •Group Anagrams
  • •Subarray Sum Equals K
  • •LRU Cache

3. Linked Lists

Patterns:

  • •Floyd's Cycle Detection (tortoise & hare)
  • •Reverse in groups
  • •Merge sorted lists

Key Problems:

  • •Reverse Linked List
  • •Detect Cycle
  • •Merge K Sorted Lists
  • •LRU Cache

4. Stacks & Queues

Patterns:

  • •Monotonic stack
  • •Next Greater Element
  • •Min/Max stack

Key Problems:

  • •Valid Parentheses
  • •Min Stack
  • •Largest Rectangle in Histogram
  • •Daily Temperatures

5. Trees & BSTs

Patterns:

  • •DFS (recursive & iterative)
  • •BFS (level-order)
  • •Tree DP
  • •Lowest Common Ancestor

Key Problems:

  • •Invert Binary Tree
  • •Validate BST
  • •Lowest Common Ancestor
  • •Serialize/Deserialize Binary Tree
  • •Maximum Path Sum

6. Heaps

Patterns:

  • •Top K elements
  • •K-way merge
  • •Median maintenance

Key Problems:

  • •Kth Largest Element
  • •Merge K Sorted Lists
  • •Find Median from Data Stream
  • •Top K Frequent Elements

7. Graphs

Patterns:

  • •DFS (path finding, cycle detection)
  • •BFS (shortest path)
  • •Topological sort
  • •Union-Find (connected components)

Key Problems:

  • •Number of Islands
  • •Course Schedule I & II
  • •Word Ladder
  • •Clone Graph
  • •Network Delay Time

8. Tries

Key Problems:

  • •Implement Trie
  • •Word Search II
  • •Design Add and Search Words Data Structure

Algorithm Patterns

1. Two Pointers

  • •Same direction (fast/slow)
  • •Opposite direction (left/right)
  • •Use Cases: Sorted arrays, palindromes, pair sums
  • •Practice: 15-20 problems

2. Sliding Window

  • •Fixed size window
  • •Variable size window
  • •Use Cases: Substring problems, max/min subarray
  • •Practice: 15-20 problems

3. Binary Search

  • •Classic binary search
  • •Binary search on answer
  • •Search in rotated arrays
  • •Practice: 20-25 problems

4. Dynamic Programming (Critical)

Subcategories:

  • •1D DP: Fibonacci, climbing stairs, house robber
  • •2D DP: Grid problems, edit distance
  • •DP on strings: Palindromes, regex matching
  • •DP on subsequences: LIS

Key Problems:

  • •Climbing Stairs
  • •House Robber I, II, III
  • •Coin Change
  • •Longest Increasing Subsequence
  • •Edit Distance
  • •Longest Common Subsequence
  • •Word Break
  • •Regular Expression Matching

Practice: 30-40 problems (MUST-FOCUS)

5. Greedy Algorithms

Key Problems:

  • •Jump Game I & II
  • •Meeting Rooms II
  • •Gas Station
  • •Task Scheduler

Practice: 15-20 problems

6. Backtracking

Key Problems:

  • •Subsets I & II
  • •Permutations I & II
  • •Combination Sum
  • •N-Queens
  • •Word Search
  • •Generate Parentheses

Practice: 20-25 problems

7. Bit Manipulation

Key Problems:

  • •Single Number
  • •Number of 1 Bits
  • •Counting Bits
  • •Sum of Two Integers

Practice: 10-15 problems

Complexity Analysis

Master Big O notation:

  • •Time: O(1), O(log N), O(N), O(N log N), O(N²), O(2^N)
  • •Space: Stack space, auxiliary space
  • •Always discuss trade-offs between time and space

Part 2: System Design (20% focus for L4)

When to Expect System Design

  • •4+ years experience
  • •Backend/infrastructure teams (Google Cloud, Ads, Search, YouTube)
  • •Resume mentions distributed systems

Expected Depth for L4

  • •Focus: Object modeling, service decomposition, basic scalability
  • •NOT Expected: Deep distributed systems, complex failure scenarios
  • •Duration: 45 minutes

Fundamental Concepts

1. Scalability Basics

  • •Vertical scaling: More CPU/RAM to single machine
  • •Horizontal scaling: More machines + load balancing
  • •Load balancing: Round-robin, least connections, consistent hashing
  • •Caching: Where to cache, invalidation strategies
  • •Database sharding: Horizontal partitioning

2. Data Storage

  • •SQL vs NoSQL: When to use each
  • •Database indexing: B-trees, query optimization
  • •Normalization: 1NF, 2NF, 3NF
  • •Replication: Master-slave, multi-master
  • •CAP theorem: Basic understanding

3. Caching Strategies

  • •Cache-aside (lazy loading)
  • •Write-through: Write to cache and DB simultaneously
  • •Write-back: Write to cache, async write to DB
  • •Cache eviction: LRU, LFU, FIFO
  • •Cache invalidation: When to invalidate

4. APIs & Communication

  • •REST vs GraphQL
  • •HTTP methods: GET, POST, PUT, DELETE
  • •Status codes: 200, 201, 400, 401, 403, 404, 500, 503
  • •API versioning: Header-based, URL-based
  • •Rate limiting: Token bucket, leaky bucket
  • •Pagination: Offset-based, cursor-based

5. Message Queues

  • •Use cases: Async processing, decoupling services
  • •Delivery guarantees: At-most-once, at-least-once, exactly-once
  • •Dead letter queues
  • •Back pressure: Handling slow consumers

6. Microservices Basics

  • •Service discovery
  • •API gateway
  • •Circuit breaker

L4 System Design Problems

Practice These (Easy-Medium):

1. URL Shortener

  • •Hash function for URL → short code
  • •Database choice
  • •Collision handling
  • •Redirect logic (301 vs 302)
  • •Basic caching

2. Rate Limiter

  • •Fixed window, sliding window, token bucket
  • •In-memory vs distributed
  • •Redis implementation

3. Parking Lot System

  • •Object modeling (classes, relationships)
  • •Spot allocation algorithm
  • •Availability tracking

4. Notification Service

  • •Email, SMS, push notifications
  • •Queue-based architecture
  • •Retry logic
  • •User preferences

5. Simple Key-Value Store

  • •Hash table basics
  • •Persistence strategies
  • •Basic caching

6. Chat Application (basics)

  • •WebSocket connections
  • •Message storage
  • •Online/offline status

System Design Approach (45 min)

1. Clarify Requirements (5-7 min)

  • •Functional requirements
  • •Non-functional requirements
  • •Assumptions

2. Back-of-envelope Estimation (3-5 min)

  • •Daily active users → requests/sec
  • •Storage requirements
  • •Bandwidth

3. High-Level Design (10-15 min)

  • •Draw: client, load balancer, servers, database, cache
  • •Explain data flow
  • •Identify bottlenecks

4. Deep Dive (15-20 min)

  • •Database schema
  • •API endpoints
  • •Caching strategy
  • •How to scale

5. Trade-offs (5 min)

  • •SQL vs NoSQL
  • •Consistency vs availability
  • •Cost vs performance

Part 3: Behavioral (20% focus)

What Google Evaluates

1. Googleyness (8 Traits)

  • •Comfort with ambiguity
  • •Humility
  • •Bias to action
  • •Ethical decision-making
  • •Ownership
  • •High standards
  • •Creative thinking
  • •Collaborative spirit

2. Leadership (Emergent Leadership)

  • •Stepping up when skills are needed
  • •Cross-functional collaboration
  • •Influencing without authority

STAR Method

Situation (10-15s): Set context Task (10-15s): Your responsibility Action (40-60s): What YOU did Result (20-30s): Quantified impact, lessons learned

Target: 90 seconds - 2 minutes per answer

Common Behavioral Questions

Teamwork & Collaboration

  1. •Time you worked with difficult team member
  2. •Time you helped a teammate
  3. •Successful collaboration

Leadership & Ownership

  1. •Time you took initiative
  2. •Time you led a project
  3. •Decision without complete information

Handling Failure & Conflict

  1. •Time you failed
  2. •Time you disagreed with a decision
  3. •Time you received critical feedback

Problem-Solving & Innovation

  1. •Complex technical problem solved
  2. •Time you improved a process
  3. •Time you learned something new quickly

Dealing with Pressure

  1. •Working under tight deadlines
  2. •Handling multiple priorities

Standard Questions

  1. •"Tell me about yourself" (2 min)
  2. •"Why Google?" (1 min)
  3. •"Why leave current role?"
  4. •"Where do you see yourself in 5 years?"
  5. •"Biggest weakness?"
  6. •"Questions for me?"

Prepare 5-7 STAR Stories

Cover these categories:

  1. •Technical achievement
  2. •Leadership/influence
  3. •Collaboration
  4. •Failure/learning
  5. •Conflict resolution
  6. •Initiative/proactivity
  7. •Handling ambiguity

For each story:

  • •2-minute version (full STAR)
  • •1-minute version (condensed)
  • •Quantified impact

Preparation Timeline

3-Month Plan (140 hours total)

Month 1: Foundation (40 hours)

  • •Week 1-2: Arrays, Strings, Hash Tables, Two Pointers (30 problems)
  • •Week 3-4: Linked Lists, Stacks, Queues, Sliding Window (30 problems)

Month 2: Advanced (50 hours)

  • •Week 1-2: Trees, Graphs, DFS/BFS (30 problems)
  • •Week 3-4: Dynamic Programming, Greedy (30 problems)

Month 3: Hard + Mocks (50 hours)

  • •Week 1-2: Hard DP, Backtracking, System Design (20 problems + 5 designs)
  • •Week 3-4: Mock interviews, review (10 problems + 5 mocks)

Total: 150-200 LeetCode problems + 10 system designs

Daily Schedule (2-3 hours/day)

Weekdays:

  • •1 hour: 1-2 LeetCode problems (timed)
  • •30 min: Review solutions, patterns
  • •30 min: Behavioral prep (STAR stories)

Weekends:

  • •1.5 hours: 2-3 LeetCode problems
  • •1 hour: System design or mock interview
  • •30 min: Review weak areas

Resources

LeetCode Prep

  1. •LeetCode Premium (Google-tagged problems)
  2. •NeetCode 150 (curated list)
  3. •Grind 75 (updated Blind 75)
  4. •AlgoExpert (pattern-based)
  5. •Educative.io - Grokking Coding Interview

System Design

  1. •Grokking System Design Interview (Educative.io)
  2. •System Design Interview Vol 1 & 2 - Alex Xu
  3. •ByteByteGo YouTube
  4. •Gaurav Sen YouTube

Behavioral

  1. •Exponent YouTube
  2. •IGotAnOffer blog
  3. •Record yourself answering

Mock Interviews

  1. •Pramp (free peer mocking)
  2. •Interviewing.io (paid)
  3. •LeetCode mock assessments

Final Tips

Coding Interview

  1. •Always clarify before coding
  2. •Think out loud - explain approach
  3. •Start with brute force, then optimize
  4. •Write clean code
  5. •Test your code
  6. •Analyze complexity
  7. •Handle edge cases
  8. •Ask questions if stuck

System Design

  1. •Don't jump to solution
  2. •Start simple, then scale
  3. •Be specific ("Redis for caching")
  4. •Discuss trade-offs
  5. •Use your experience
  6. •Draw diagrams
  7. •Listen to hints

Behavioral

  1. •Be genuine
  2. •Focus on YOU ("I did X")
  3. •Quantify impact
  4. •Show growth from failures
  5. •Practice out loud
  6. •Stay positive
  7. •Show enthusiasm

General

  1. •Consistency > intensity
  2. •Track progress (spreadsheet)
  3. •Review mistakes
  4. •Simulate interview conditions
  5. •Stay healthy
  6. •Build confidence

Key Strengths to Highlight

If you have production experience, emphasize:

  1. •Production systems - Scaled SaaS apps
  2. •Queue systems - Message queues, retry logic
  3. •Database optimization - Query optimization, indexing
  4. •Caching architecture - Redis patterns
  5. •Container orchestration - Kubernetes, ECS
  6. •Leadership - Led teams, code reviews
  7. •Full ownership - End-to-end product building

Connect stories back to these strengths!

Good luck! Focus on mastering DSA patterns and you'll be well-prepared! 🚀

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