Intuit vs eBay: Interview Question Comparison

When preparing for technical interviews at major tech companies, understanding their specific question patterns and focus areas can significantly improve your efficiency. Intuit and eBay, while both established tech giants, show distinct differences in their interview question profiles that warrant strategic preparation. Intuit's dataset contains 71 questions with a heavier emphasis on medium and hard problems, while eBay's 60 questions lean slightly more toward easier problems but maintain a strong focus on core data structures.

Question Volume and Difficulty

Intuit's question bank is both larger and more challenging. With 71 total questions (10 Easy, 47 Medium, 14 Hard), approximately 66% of their problems are at the Medium level or above. This suggests Intuit interviews often probe deeper into algorithmic optimization and complex problem-solving. You should expect follow-up questions that test edge cases and efficiency improvements.

eBay's profile, with 60 questions (12 Easy, 38 Medium, 10 Hard), is slightly less daunting. While still rigorous, the higher proportion of Easy questions (20% vs. Intuit's 14%) and slightly lower total count indicates a strong focus on foundational correctness and clean code, though Medium problems remain the core of the interview.

Example of a Medium-difficulty array problem common to both:

# Find the maximum sum of a contiguous subarray (Kadane's Algorithm)
def maxSubArray(nums):
    max_current = max_global = nums[0]
    for num in nums[1:]:
        max_current = max(num, max_current + num)
        max_global = max(max_global, max_current)
    return max_global

Topic Overlap

Both companies heavily test Array, String, and Hash Table problems. These form the essential core for both interview loops. Mastering operations like two-pointer techniques, sliding window, and frequency mapping is non-negotiable.

The key difference is Dynamic Programming (DP). Intuit explicitly lists DP as a top topic, while eBay's listed top topics do not. This doesn't mean DP never appears at eBay, but it indicates Intuit places a higher, more consistent priority on it. Preparing for Intuit requires dedicated DP practice on classical problems like knapsack, longest common subsequence, and coin change.

Example of a classic DP problem more likely at Intuit:

# Coin Change (Minimum coins to make amount)
def coinChange(coins, amount):
    dp = [float('inf')] * (amount + 1)
    dp[0] = 0
    for coin in coins:
        for x in range(coin, amount + 1):
            dp[x] = min(dp[x], dp[x - coin] + 1)
    return dp[amount] if dp[amount] != float('inf') else -1

eBay's inclusion of Sorting as a top topic suggests a focus on problems where ordering, searching, or merging datasets is central, often combined with other techniques.

Which to Prepare for First

Prepare for Intuit first. Its question bank is broader and includes the additional, challenging topic of Dynamic Programming. If you can handle Intuit's profile—solving a high volume of Medium problems and several Hard DP questions—you will be well-equipped for eBay's core topics. The reverse is not as true; focusing only on eBay's list might leave gaps for Intuit's DP emphasis.

A logical strategy is:

1. Solidify fundamentals in Arrays, Strings, and Hash Tables (common to both).
2. Deeply practice Dynamic Programming patterns.
3. Refine with Sorting-based problems and a final review of eBay's specific question trends.

This approach maximizes your coverage and ensures you're ready for the more demanding of the two interview loops.

For specific company question lists, visit the Intuit question page and the eBay question page.