How to Crack Grubhub Coding Interviews in 2026

Grubhub’s technical interview process is designed to assess your ability to solve practical, real-world problems with clean, efficient code. You can expect a series of virtual coding interviews focusing on data structures and algorithms, often with a slant toward problems involving spatial data, order management, and system design—reflecting their core delivery logistics platform. Success hinges on a focused, pattern-based preparation strategy.

By the Numbers — Difficulty Breakdown and What It Means

The data reveals a clear, consistent pattern: Grubhub’s coding interviews are dominated by Medium difficulty problems. With 100% of questions falling into this category, the expectation is not that you solve obscure, complex puzzles, but that you can reliably and competently implement optimal solutions to common algorithmic challenges under time pressure. This means you must have a strong command of fundamental data structures and the ability to recognize which pattern applies to a slightly novel problem statement. The absence of Easy and Hard questions suggests the interview is a test of consistent engineering proficiency rather than basic knowledge or exceptional genius.

Top Topics to Focus On

The most frequent topics—Array, Sorting, Depth-First Search (DFS), Breadth-First Search (BFS), and Union-Find—paint a picture of Grubhub’s problem domain. You’re likely to encounter scenarios involving geographic points (arrays of coordinates), scheduling or ordering tasks (sorting), navigating grids or networks (DFS/BFS), and grouping connected elements (Union-Find).

• Array & Sorting: Many problems start with an array of data points—like delivery locations or time slots—that require processing. Sorting is often the first step to enable efficient two-pointer or greedy solutions.
• Depth-First Search (DFS) & Breadth-First Search (BFS): These are fundamental for traversal, whether you're exploring all possible delivery routes (DFS backtracking) or finding the shortest path on a grid representing a city map (BFS).
• Union-Find (Disjoint Set Union): This is a critical, high-value data structure for problems involving dynamic connectivity. At Grubhub, this could model which delivery zones are connected or group orders from the same restaurant.

Given the prevalence of traversal and connectivity, mastering a template for BFS on a grid is essential. This pattern is directly applicable to "shortest path" problems, a common theme in logistics.

from collections import deque

def bfs_shortest_path(grid, start, target):
    if not grid:
        return -1
    rows, cols = len(grid), len(grid[0])
    # Directions: up, down, left, right
    directions = [(1,0), (-1,0), (0,1), (0,-1)]
    queue = deque([(start[0], start[1], 0)])  # (row, col, distance)
    visited = set([(start[0], start[1])])

    while queue:
        r, c, dist = queue.popleft()
        # Check if target is reached
        if (r, c) == (target[0], target[1]):
            return dist
        # Explore neighbors
        for dr, dc in directions:
            nr, nc = r + dr, c + dc
            if (0 <= nr < rows and 0 <= nc < cols and
                grid[nr][nc] != '#' and  # '#' represents an obstacle
                (nr, nc) not in visited):
                visited.add((nr, nc))
                queue.append((nr, nc, dist + 1))
    return -1  # Target not reachable

Preparation Strategy — A 4-6 Week Study Plan

Weeks 1-2: Foundation & Core Topics. Dedicate this phase to the top five topics. For each, study the core theory and memorize the implementation pattern for its most common data structure (e.g., BFS queue, DFS recursion/stack, Union-Find array). Solve 10-15 curated Medium problems for these topics alone.

Weeks 3-4: Pattern Integration & Practice. Start mixing topics. Solve problems that combine patterns, like "Sort the array first, then use two-pointer" or "Use BFS on a grid derived from an array of points." Begin timing your sessions (45 minutes per problem) to simulate the interview. Complete 2-3 mock interviews.

Weeks 5-6: Refinement & Company-Specific Prep. In the final stretch, focus exclusively on Medium-difficulty problems. Re-solve problems you struggled with. Dedicate several sessions to practicing only problems tagged with Grubhub or similar logistics/delivery companies to attune your thinking to their domain.

Key Tips

1. Prioritize Correctness and Clarity First. Given the Medium-difficulty focus, interviewers expect a bug-free, well-structured solution. Start with a brute-force approach if necessary, explain it, then optimize. Clean, readable code with good variable names is more valuable than a clever but opaque one-liner.
2. Verbally Connect the Problem to Grubhub's Domain. When explaining your solution, briefly note how the algorithm might apply to a real Grubhub system—e.g., "This BFS would efficiently find the nearest driver to a restaurant." This shows practical insight.
3. Practice Union-Find Until It's Automatic. It's a less common topic in general prep but a high-frequency one here. Be able to write the find and union operations with path compression and union by rank without hesitation.
4. Manage Your Time Relentlessly. Spend no more than 5-10 minutes on problem clarification and brainstorming. Leave a solid 20-25 minutes for coding and 5-10 minutes for testing and discussion. A complete, well-explained Medium solution is the goal.

By focusing your practice on these high-probability topics and patterns, you build the specific muscle memory needed to succeed in Grubhub's interviews. Consistency with Medium problems is your greatest asset.

Browse all Grubhub questions on CodeJeet