Amazon vs Meta: Interview Question Comparison

When preparing for technical interviews at top tech companies, understanding their specific focus areas can dramatically increase your efficiency. Amazon and Meta (Facebook) are two giants with distinct engineering cultures, which is reflected in their interview question patterns. While there is significant overlap in the core data structures tested, the volume, difficulty distribution, and subtle emphasis differ. A strategic candidate will tailor their preparation to these nuances.

Question Volume and Difficulty

The raw data shows Amazon has a larger overall question pool and a heavier emphasis on harder problems.

• Amazon: With 1,938 total questions, Amazon's breakdown is Easy: 530, Medium: 1,057, Hard: 351. The Medium and Hard categories constitute over 72% of their catalog. This suggests Amazon interviews are designed to rigorously test problem-solving under pressure, often with follow-up questions that increase in complexity.
• Meta: With 1,387 total questions, Meta's breakdown is Easy: 414, Medium: 762, Hard: 211. While still challenging, the proportion of Hard questions is lower (15% vs. Amazon's 18%). Meta's focus appears slightly more balanced, though Medium problems remain the core of the interview.

This difference implies that for Amazon, you must be exceptionally solid on Medium problems and comfortable tackling a significant number of Hard ones. For Meta, deep mastery of Medium problems is absolutely critical.

Topic Overlap

Both companies heavily test foundational data structures. Array, String, and Hash Table problems are paramount for both. This is the core of most coding interviews.

• Amazon's Additional Focus: Dynamic Programming (DP). Amazon's inclusion of DP as a top topic is a key differentiator. Expect problems involving optimization, counting, or combinatorial decisions. You must be prepared to identify overlapping subproblems and optimal substructure.
• Meta's Additional Focus: Math. Meta's listing of Math highlights a focus on logical reasoning, number manipulation, and sometimes combinatorial mathematics. This can involve problems related to number theory, probability, or clever arithmetic solutions.

Here is a typical problem that could appear at either company, followed by examples of their unique emphasis.

# Overlap Example: Two Sum (Hash Table)
def two_sum(nums, target):
    seen = {}
    for i, num in enumerate(nums):
        complement = target - num
        if complement in seen:
            return [seen[complement], i]
        seen[num] = i
    return []

# Amazon Emphasis: DP (Coin Change)
def coin_change(coins, amount):
    dp = [float('inf')] * (amount + 1)
    dp[0] = 0
    for coin in coins:
        for i in range(coin, amount + 1):
            dp[i] = min(dp[i], dp[i - coin] + 1)
    return dp[amount] if dp[amount] != float('inf') else -1

# Meta Emphasis: Math (Reverse Integer)
def reverse(x):
    INT_MAX, INT_MIN = 2**31 - 1, -2**31
    rev = 0
    sign = -1 if x < 0 else 1
    x = abs(x)
    while x != 0:
        pop = x % 10
        x //= 10
        # Check for overflow before multiplying
        if rev > (INT_MAX // 10) or (rev == INT_MAX // 10 and pop > 7):
            return 0
        rev = rev * 10 + pop
    return rev * sign

Which to Prepare for First

Prepare for Amazon first. Here’s why: Amazon's broader and deeper question pool, with its significant Dynamic Programming requirement, represents a superset of the core skills needed for Meta. Mastering Amazon-level problems—especially Medium and Hard DP, Array, and String questions—will make you over-prepared for Meta's Math-focused problems and strong on the shared Hash Table, Array, and String fundamentals.

A logical study path is:

1. Build a rock-solid foundation in Arrays, Strings, and Hash Tables.
2. Dive deeply into Dynamic Programming patterns (0/1 Knapsack, LCS, etc.).
3. Practice Amazon's large set of Medium problems.
4. Then, shift focus to Meta-specific Math problems and refine your system design and behavioral skills (Amazon's Leadership Principles vs. Meta's "Move Fast" culture).

This approach ensures you are ready for the more statistically difficult interview and then can specialize.

For targeted practice, visit the Amazon and Meta question lists: Amazon Interview Questions | Meta Interview Questions