Array Questions at eBay: What to Expect

Array questions dominate eBay’s technical interviews, making up 35 of the 60 most frequently asked problems. This focus isn’t arbitrary. eBay’s core marketplace, search, and logistics systems process vast streams of transactional and inventory data—fundamentally represented and manipulated as arrays, lists, or sequences. Mastery of array manipulation is a direct proxy for a candidate’s ability to handle real-time data processing, optimize item listings and searches, and implement efficient sorting and filtering logic. Simply put, if you can’t solve array problems efficiently, you’ll struggle with eBay’s domain-specific challenges.

What to Expect — Types of Problems

The array problems at eBay typically fall into a few key categories, often with a practical twist.

Two-Pointer and Sliding Window: These are ubiquitous. Expect questions on finding pairs in sorted data (like matching buyer and seller price ranges), calculating running metrics over a sequence (e.g., average delivery time over a window), or dealing with subarrays. A classic is finding the longest subarray with a sum constraint, mimicking resource allocation or session analysis.

Sorting and Searching: Given eBay’s massive datasets, efficient lookup and ordering are critical. Problems often involve variations on binary search (e.g., finding the insertion point for a new auction bid in a sorted list) or custom sorting logic (e.g., ordering search results by relevance, price, and time).

In-Place Array Manipulation: Questions that require modifying an array without extra space are common, testing your grasp of memory efficiency. This includes tasks like segregating items (e.g., separating in-stock from out-of-stock products) or applying cyclic rotations, which relate to data shuffling in distributed systems.

Prefix Sum and Hashing: These techniques are essential for optimizing repeated range queries or quick lookups—common in analytics and feature calculation. You might need to find a contiguous subarray with a specific sum (tracking transaction totals) or identify duplicate/unique elements in user activity logs.

How to Prepare — Study Tips with One Code Example

Focus on pattern recognition, not memorization. For each problem type, learn the underlying algorithm template. Then, practice applying it to at least 3-5 variations. Always articulate your thought process and discuss time/space complexity first.

A fundamental pattern is the Sliding Window for finding a subarray meeting a condition. Here’s a template for finding the smallest subarray with a sum at least K:

def smallest_subarray_sum(s, arr):
    min_length = float('inf')
    window_sum = 0
    left = 0

    for right in range(len(arr)):
        window_sum += arr[right]  # Expand window
        while window_sum >= s:    # Shrink while condition met
            min_length = min(min_length, right - left + 1)
            window_sum -= arr[left]
            left += 1
    return 0 if min_length == float('inf') else min_length

Recommended Practice Order

1. Foundation: Start with basic two-pointer (e.g., two-sum), in-place operations (move zeroes), and simple sliding window (maximum sum subarray of size K).
2. Core Patterns: Progress to more complex sliding window (dynamic size, like the example above), prefix sum applications, and cyclic sort problems.
3. Search & Efficiency: Tackle rotated array binary search and problems requiring optimization with hash maps.
4. eBay Context: Finally, practice problems that combine patterns, simulating multi-step data processing tasks relevant to e-commerce.

Practice Array at eBay