How to Crack FAANG Interviews (Part - 2)

Everything you need to prepare smarter, not harder: real patterns, real resources, and a 5-week training system.

A month ago, I gave my interview at Amazon, and the prep taught me something important: it’s not just about passing interviews, but it’s about thinking like Amazon.

FAANG interviews are tough, but they're not unpredictable.

If you understand what each company prioritizes, like how Amazon builds warehouses, handles supply chains, and optimizes delivery, you’ll notice a clear pattern in the questions they ask.

This isn’t about grinding 300+ problems randomly.

It’s about solving the right patterns, using real interview tags, company logic, and a 5-week strategy.

In Part 2, we’ll break down Amazon

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Amazon

Key Question Patterns & Company Focus

• Trees & Binary Search Trees (Amazon warehouses, inventory, hierarchical data)

• Heaps & Priority Queues (order processing, cost optimization)

• Graphs & BFS/DFS (supply-chain networks)

• Dynamic Programming & Greedy (resource allocation, path minimization)

• Hash Tables, Sorting & Searching (catalog indexing, fast lookups)

Resource List

• Books

  • Cracking the Coding Interview

  • Elements of Programming Interviews (EPI)

• Online Platforms & Tags

  • LeetCode “Amazon” Tag

  • GeeksforGeeks Amazon Interview Experience

• Articles & Blogs

  • How to Crack Amazon SDE Interview

• YouTube Channels & Playlists

  • NeetCode (@NeetCode) – search “NeetCode Amazon”

  • TechLead (@TechLead) – search “TechLead Amazon interview tips”

5-Week Training Plan

Week 1 – Arrays, Hash Tables & Easy “Amazon” Problems

• Goals

  • Master array manipulations, frequency counting, prefix sums, two-sum variants

  • Build fluency with hash maps (distinct counts, O(1) lookup, collision handling)

• Problems (12 Easy/Medium)

  1. Two Sum

  2. Subarray Sum Equals K

  3. Product of Array Except Self

  4. Valid Sudoku

  5. Group Anagrams

  6. Top K Frequent Elements

  7. Sort Characters By Frequency

  8. Intersection of Two Arrays II

  9. Contains Duplicate II

  10. Valid Anagram

  11. Happy Number

  12. First Unique Character in a String

• Study Actions

  1. Solve in ≤ 20 minutes; review if > 20 minutes

  2. Write down hash map edge cases (null, duplicates, large ranges)

  3. Re-implement from scratch three times by hand

Week 2 – Trees & Binary Search Trees (BST)

• Goals

  • Master tree traversal, BFS-level order, recursive/iterative DFS

  • Understand BST invariants and common BST queries (search, insert, delete, kth smallest)

• Problems (10 Medium)

  1. Invert Binary Tree

  2. Validate Binary Search Tree

  3. Kth Smallest Element in a BST

  4. Binary Tree Zigzag Level Order Traversal

  5. Lowest Common Ancestor of a BST

  6. Serialize and Deserialize Binary Tree

  7. Maximum Depth of Binary Tree

  8. Binary Tree Level Order Traversal

  9. Populating Next Right Pointers in Each Node

  10. Diameter of Binary Tree

• Study Actions

  1. Draw 5–6 small trees; perform inorder/preorder/postorder on paper

  2. Write iterative BFS/DFS (stack/queue) in ≤ 15 minutes

  3. For BST problems, sketch tree shape and validate pointers

Week 3 – Heaps, Sorting & Basic Dynamic Programming

• Goals

  • Understand heap operations (push/pop) in O(log n)

  • Master DP templates (1D knapsack, LIS)

  • Reinforce sorting algorithms (quick/merge) and their trade-offs

• Problems (10 Medium)

  1. Kth Largest Element in an Array

  2. Top K Frequent Elements (if not done in Week 1)

  3. Sort Characters By Frequency (if not done in Week 1)

  4. Merge Intervals

  5. Meeting Rooms II

  6. House Robber

  7. Climbing Stairs

  8. Longest Common Subsequence

  9. Coin Change

  10. Word Break

• Study Actions

  1. Implement a min-heap from scratch or use built-in; note complexities

  2. Write DP recurrence relations by hand (e.g., dp[i] = max(dp[i−1], dp[i−2]+nums[i]))

  3. Time each DP solution; verify O(N×M) or O(N log N)

Week 4 – Graphs & Advanced Dynamic Programming

• Goals

  • Master BFS/DFS on directed/undirected graphs, cycle detection, topological sort

  • Cover advanced DP (2D DP: matrix path, edit distance)

  • Solve graph + DP mixed problems in ≤ 35 minutes

• Problems (10 Medium/Hard)

  1. Number of Islands (if not done)

  2. Course Schedule (or II)

  3. Word Ladder

  4. Word Search

  5. Longest Increasing Path in a Matrix

  6. Minimum Size Subarray Sum

  7. Longest Substring with At Most K Distinct Characters

  8. Edit Distance

  9. Unique Paths

  10. Word Search II (if not done in Week 3)

• Study Actions

  1. Write Kahn’s algorithm & DFS cycle detection from scratch

  2. Trace DP tables on paper for edit distance & unique paths

  3. Optimize recursive solutions with memoization; compare top-down vs. bottom-up

Week 5 – Mock Interviews & Feedback Loop

• Goals

  • Simulate 3 timed “Amazon” mocks (45 minutes each)

  • Identify bottlenecks (slow DP transitions, graph pitfalls)

  • Sharpen verbal explanation: articulate time/space trade-offs

• Actions & Platforms

  1. Peer Mock: Rotate roles; keep strict time

  2. Online Mock:

     • Pramp – search “Amazon”

  3. Self-Review:

     • List problems that took > 30 minutes

     • Re-solve in ≤ 25 minutes

     • Record audio of your explanation; critique clarity

Final Thoughts

The truth is that every FAANG company follows a repeatable pattern, once you study their previous interviews and product-specific needs.

Use this breakdown like a GPS: you still have to drive, but you’ll always know the fastest route.

In Part 3, we’ll tackle Apple.

Until next week,

Jugaldb