How to Crack Chewy Coding Interviews in 2026

Chewy’s technical interview process is designed to assess practical problem-solving skills and coding fluency. Candidates typically face a series of coding rounds focusing on algorithmic challenges, often with a strong emphasis on data manipulation and optimization—key skills for an e-commerce platform handling massive inventory and customer data. Success here hinges on a targeted understanding of their preferred question style.

By the Numbers — Difficulty Breakdown and What It Means

The data reveals a clear pattern: 80% Medium and 20% Easy questions, with no Hards. This breakdown is strategic. Chewy isn't looking for obscure algorithmic geniuses; they are evaluating strong, reliable engineers who can cleanly solve common but non-trivial problems under interview conditions. The absence of Hard questions means your preparation should prioritize breadth and mastery over depth in esoteric topics. You must be able to dissect a typical Medium problem—often involving multiple concepts like arrays and hash tables—and implement a robust solution efficiently. The 20% Easy questions serve as a baseline check for coding competency and attention to detail.

Top Topics to Focus On

Your study should be laser-focused on these five areas, which form the core of Chewy's question bank.

• Array: Fundamental to almost all data processing. Expect problems involving traversal, in-place modification, and sliding windows.
• Hash Table: The go-to tool for achieving O(1) lookups to optimize time complexity. It's frequently paired with arrays to solve two-sum variants or count frequencies.
• Sorting: Often a prerequisite step for more complex algorithms like two-pointer solutions or divide and conquer. Knowing the implications of sorting on time complexity is crucial.
• Divide and Conquer: A powerful paradigm for problems like efficient searching (binary search) or advanced sorting (merge/quick sort), which break problems into manageable sub-problems.
• Heap (Priority Queue): Essential for problems requiring constant access to the "top K" or "minimum/maximum" elements, such as merging sorted lists or finding medians in a stream.

The most critical pattern to master is combining a Hash Table with an Array to track indices or counts. This is the cornerstone of countless Medium-difficulty problems.

def two_sum(nums, target):
    seen = {}  # Hash Table: value -> index
    for i, num in enumerate(nums):  # Array traversal
        complement = target - num
        if complement in seen:
            return [seen[complement], i]
        seen[num] = i
    return []

# Example: Find indices of two numbers that add to target.
# nums = [2, 7, 11, 15], target = 9 -> [0, 1]

Preparation Strategy — A 4-6 Week Study Plan

A structured approach is key to covering the necessary ground without burnout.

Weeks 1-2: Foundation & Core Topics. Dedicate deep-dive days to each of the top five topics. For each, learn the theory, standard implementations, and solve 8-10 curated problems focusing on Easy and Medium difficulty. Start with array/hash table combinations.

Weeks 3-4: Pattern Integration & Mock Interviews. Stop studying topics in isolation. Practice solving mixed-topic Medium problems that mimic a real interview. For example, a problem requiring sorting an array first, then using a two-pointer technique. Begin doing timed mock interviews twice a week.

Weeks 5-6: Company-Specific Practice & Refinement. Solve all available Chewy-labeled questions. Revisit problems you struggled with. In your final mock interviews, explicitly state your thought process aloud, as you will need to during the actual interview. Focus on writing clean, production-ready code with clear variable names.

Key Tips

1. Optimize for Readability First. Chewy's engineers need to maintain code. Write clear, well-structured code with sensible variable names (customerIds not arr1) over clever, one-line solutions. Comment briefly on complex logic.
2. Always Discuss Trade-offs. When presenting your solution, verbally note the time and space complexity. If there's a brute-force approach, mention it and explain why you're optimizing. This demonstrates system thinking.
3. Validate Input and Ask Questions. Before coding, confirm edge cases: Can the array be empty? Are numbers negative? This shows professional diligence and prevents simple bugs.
4. Practice with Real Data Structures. Implement heaps (priority queues) and hash maps from scratch at least once to understand their internals. This deep knowledge helps when you need to modify a standard approach.

Mastering these patterns and executing this focused plan will position you strongly for Chewy's coding interviews. The goal is consistent, clean, and communicable solutions.

Browse all Chewy questions on CodeJeet