Greedy Questions at Rubrik: What to Expect

Greedy algorithms are a small but critical part of Rubrik's technical interview repertoire. With 4 out of their 37 cataloged questions tagged as Greedy, you have a roughly 1 in 10 chance of encountering one. While not the most frequent category, its presence is significant because these questions are excellent filters for assessing a candidate's problem-solving intuition and ability to reason about optimal local choices. At a company like Rubrik, which builds data management and recovery solutions, the underlying principles of greedy algorithms—making efficient, immediate decisions with system resources—mirror real-world optimization challenges in scheduling backups, managing storage, or prioritizing network traffic. Successfully solving a greedy problem demonstrates you can identify the core property that makes a simple, step-by-step approach globally optimal, a valuable skill for designing efficient systems.

What to Expect — Types of Problems

Rubrik's greedy questions typically fall into predictable patterns. The most common is Interval Scheduling and its variants, where you must select a maximum number of non-overlapping intervals or assign resources to tasks. This directly relates to scheduling jobs in a backup system. Another frequent pattern is "Greedy Choice on Sorted Data," where the key insight is to sort the input array by a specific criterion (like end time, ratio, or cost) and then make a series of optimal picks. You might also see problems involving minimum cost or maximum gain from a sequence of actions, often requiring a clever sorting key or a priority queue to manage choices. The constraints are usually designed so the greedy approach is valid, but the interviewer will expect you to justify why your algorithm is correct, not just implement it.

How to Prepare — Study Tips with One Code Example

To prepare, focus on mastering the standard greedy patterns, not memorizing solutions. For each problem, practice articulating the greedy choice property and proving optimality. Start by recognizing the problem type: if it asks for "maximum number of tasks" or "minimum number of resources," think greedy. Always consider if sorting the input unlocks the solution.

A fundamental pattern is the classic Interval Scheduling (Maximum Number of Non-Overlapping Intervals). The greedy choice is to always pick the interval that ends the earliest, as this leaves the most room for future intervals.

def max_non_overlapping_intervals(intervals):
    # Sort intervals by their end time
    intervals.sort(key=lambda x: x[1])
    count = 0
    last_end = float('-inf')

    for start, end in intervals:
        if start >= last_end:  # Non-overlapping
            count += 1
            last_end = end
    return count

Recommended Practice Order

Build your competency in this logical order:

1. Foundations: Start with classic problems like Interval Scheduling (above), Assign Cookies, and Maximum Subarray (Kadane's Algorithm, a greedy variant).
2. Sorting-Centric Problems: Move to problems where the main trick is sorting by a custom key, such as Minimum Number of Arrows to Burst Balloons or Meeting Rooms II.
3. Priority Queue Greedy: Practice problems that require a heap to manage the "best" current choice, like Task Scheduler or merging sorted lists.
4. Rubrik-Specific: Finally, tackle the actual greedy questions in Rubrik's question bank to familiarize yourself with their style and difficulty.

Mastering these patterns will allow you to efficiently identify and solve the greedy problems you encounter.

Practice Greedy at Rubrik