Greedy Questions at Salesforce: What to Expect

Greedy algorithms appear in about 12% of Salesforce's technical interview question pool (23 out of 189). While not the most frequent category, they are a consistent and important filter. These problems test your ability to identify optimal substructure and make a series of locally optimal choices that lead to a globally optimal solution. For a company like Salesforce, which builds complex, scalable platforms, this mirrors real-world optimization challenges in resource scheduling, data routing, and cost minimization within their cloud services. Demonstrating a clean, efficient greedy solution shows you can think practically about system constraints and performance.

What to Expect — Types of Problems

Salesforce's greedy questions tend to focus on practical, business-adjacent optimization rather than abstract mathematical puzzles. You can expect two main types:

1. Interval Problems: These are classic. You might be asked to schedule the maximum number of non-overlapping meetings (a common Salesforce scenario) or find the minimum number of resources (like servers or support agents) needed to cover all tasks. The greedy strategy typically involves sorting by end times.
2. Assignment & Partitioning Problems: These involve optimally assigning or grouping items. Examples include dividing a sequence into segments with minimum cost, or assigning tasks to workers under specific constraints. The greedy choice often involves sorting by a key metric (like difficulty or duration) and processing items in order.

The problems are designed to be solvable within a 30-45 minute interview slot, meaning the greedy approach, once identified, is usually straightforward to implement.

How to Prepare — Study Tips with One Code Example

Your preparation should focus on pattern recognition. Don't memorize problems—learn the decision rules. For any problem, ask: "If I sort the data by a specific property, will taking the 'best' available item at each step lead to the correct answer?" Start by mastering the foundational interval scheduling problem.

The key pattern for maximum non-overlapping intervals is: sort intervals by their ending time, iterate through them, and always pick the next interval that starts after the last one ends.

def max_non_overlapping_intervals(intervals):
    if not intervals:
        return 0
    # Sort by end time
    intervals.sort(key=lambda x: x[1])
    count = 1
    last_end = intervals[0][1]

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

Recommended Practice Order

Build competence progressively:

1. Foundations: Start with classic problems: Interval Scheduling (above), Minimum Number of Arrows to Burst Balloons, and Assign Cookies.
2. Medium Variations: Move to problems like Merge Intervals, Partition Labels, and Task Scheduler. These add slight twists to the core patterns.
3. Salesforce-Specific: Finally, practice directly from the curated list of Salesforce-tagged greedy problems on platforms like CodeJeet. This acclimates you to their problem style and difficulty level.

Always verbalize your reasoning during practice. Explain why the greedy choice is safe and prove optimality, even if briefly. This is critical for the interview.

Practice Greedy at Salesforce