Uber vs Salesforce: Interview Question Comparison

When preparing for technical interviews, company-specific question patterns matter. Both Uber and Salesforce test core data structures and algorithms, but their interview approaches differ in volume, difficulty distribution, and emphasis. Understanding these differences helps you allocate your preparation time strategically.

Question Volume and Difficulty

Uber’s question bank is significantly larger and more challenging. With 381 cataloged questions, it nearly doubles Salesforce’s 189. The difficulty distribution reveals a heavier focus on medium and hard problems.

Uber (E54/M224/H103): Medium questions (224) form the core of their interview loop, often involving multi-step reasoning on real-world scenarios like dispatch logic or route optimization. The high number of hard problems (103) indicates that senior or specialized roles will face complex algorithmic design.

Salesforce (E27/M113/H49): The distribution is more moderate. Medium questions (113) are the majority, but the count of hard problems (49) is roughly half of Uber’s. This suggests a slightly more accessible interview process, though still rigorous.

Implication: Preparing for Uber requires grinding more problems, especially at the medium and hard levels. For Salesforce, a strong grasp of medium-difficulty fundamentals is paramount.

Topic Overlap

Both companies heavily test the same four core topics: Array, String, Hash Table, and Dynamic Programming. This overlap is excellent news—mastering these areas serves you for both interviews.

• Array & String: Expect manipulations, searching, and sliding window problems.
• Hash Table: Used for frequency counting, lookups, and complement searches (like Two Sum).
• Dynamic Programming: Tests optimal substructure thinking, common in problems about maximizing value or minimizing cost.

The key difference is often in the problem framing. Uber questions frequently incorporate system design elements or real-time constraints, even in coding rounds. A problem about merging intervals might be framed as merging ride schedules. Salesforce problems may relate more to data processing, CRUD logic, or business rule enforcement.

Here is a classic "Two Sum" example, a problem type common at both companies:

def two_sum(nums, target):
    seen = {}
    for i, num in enumerate(nums):
        complement = target - num
        if complement in seen:
            return [seen[complement], i]
        seen[num] = i
    return []

# Example: Find two ride durations that sum to a target time.

Which to Prepare for First

Prepare for Uber first. This is the higher-barrier exam. If you can handle Uber's volume and difficulty, you will be over-prepared for Salesforce's core technical screen. Your study priority should be:

1. Solidify Fundamentals: Master array/string operations, hash table applications, and core DP patterns (knapsack, LCS, etc.).
2. Practice Uber's Medium-Hard Problems: Use their tagged questions to get accustomed to their problem scope and complexity.
3. Adapt for Salesforce: Before a Salesforce interview, review their specific question list to understand their problem framing, but the core algorithmic skills will already be in place.

This approach is efficient. It builds the maximum required competency first, which is then transferable to the slightly less demanding interview.

For targeted practice, visit the company pages: Uber Interview Questions and Salesforce Interview Questions.