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rippling·Software Engineer·Technical Phone Screen·Intermediate

IntermediatePrefer not to say
Apr 2026Remote

Summary

Rippling SWE interview with a payroll system design question. Pretty focused session, one meaty problem the whole time, and they cared a lot about the complexity targets they gave you upfront.

Questions Asked (1)

Q1

Design and implement a payroll system for food delivery drivers that supports registering a driver with an hourly wage, computing pay for a given shift using start and end epoch timestamps, and tracking a running total across all drivers. Target O(1) for registration and pay computation.

System DesignAlgorithms & Data StructuresTechnical Trade-offs
Author's notes

The complexity constraints were printed right there in the problem and i still fumbled around for a bit before realizing there was nothing clever to do.

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AI HintsAI Generated

Suggested Approach

Start by clarifying requirements and constraints, then propose a design using a hash map for O(1) driver registration and pay computation, with a running total updated on each shift. Implement a Driver class storing hourly wage and a PayrollSystem managing drivers and total payout, ensuring all operations are constant time.

Pro tip: Mention that O(1) pay computation assumes the shift duration is computed from timestamps in constant time, and highlight that the running total is updated incrementally to avoid O(n) aggregation. Also, discuss edge cases like overlapping shifts or negative durations to show thoroughness.

1. Clarify Requirements and Constraints

Ask about expected input formats, whether shifts can overlap, if wages can change, and if the running total should be per driver or global. Confirm that O(1) is required for registration and pay computation.

2. Design Data Structures

Use a hash map (dictionary) to store drivers by ID for O(1) registration and lookup. Each driver object stores hourly wage and optionally a running total of their own pay. Maintain a global running total as a variable.

3. Implement Core Operations

For registration, insert into the hash map. For pay computation, calculate duration as (end - start) in hours, multiply by wage, add to driver's total and global total, and return the pay. All operations are O(1).

4. Handle Edge Cases and Trade-offs

Discuss handling invalid timestamps (end < start), zero-duration shifts, and concurrent updates. Mention that O(1) assumes no need to aggregate across drivers for each computation, and that the running total is updated incrementally.

5. Test and Validate

Walk through a simple example: register driver with wage, compute pay for a shift, verify running total. Suggest unit tests for edge cases and performance tests to confirm O(1).

Key Points to Mention

  • Use of hash map for O(1) driver registration and lookup
  • Constant-time pay computation using timestamp difference and multiplication
  • Incremental update of running total to avoid O(n) aggregation
  • Handling of edge cases like invalid timestamps and zero-duration shifts
  • Discussion of concurrency if multiple shifts are processed simultaneously
  • Trade-offs: memory vs. speed, and assumptions about wage changes

AI-generated suggestions, not part of the candidate's original notes. May be inaccurate — verify before relying on them.