Katkat
Back

Design several backend components

RipplingSoftware Engineer · HR Screen
HardSoftware EngineerHR ScreenSoftware Engineering Fundamentals

Last updated

This problem tests your ability to design a robust backend architecture for an employee management system, focusing on data consistency, audit logging, and extensible API design.

The Problem

Design the backend infrastructure for a modern HR platform that handles employee records, payroll adjustments, and leave requests. The system must support the following components:

  1. Data Model: Design a database schema for an Employee entity and a PayrollAdjustment entity. How would you handle historical changes (e.g., salary updates) while maintaining an audit trail?
  2. Concurrency: Imagine two administrators attempt to approve a leave request at the exact same time. How do you prevent double-processing or conflicting state changes?
  3. Extensibility: The system needs to support custom fields for different regions (e.g., specific tax codes for different states). Design a database pattern that supports this without requiring frequent schema migrations.

Constraints and Requirements

  • Provide a high-level API design (e.g., RESTful endpoints) for updating an employee's salary.
  • Explain how you would ensure auditability (who changed what and when).
  • Assume a scale of 100,000 employees and high write volume during payroll processing cycles.

Example Context

If an employee's salary is changed on Monday, a payroll run on Friday must calculate the pro-rated amount correctly. The audit log must show the old value, the new value, the timestamp, and the actor ID for every transaction.

Hints

Hint 1

Consider using an append-only transaction log or a dedicated audit table rather than just updating a single 'current salary' column.

Hint 2

Look into optimistic locking (using version columns or timestamps) to handle race conditions during concurrent updates.

Hint 3

For flexible schema design, consider using a JSONB column in a relational database or an Entity-Attribute-Value (EAV) model, and discuss the trade-offs of each.

Follow-up questions

  • How would you handle a scenario where a downstream payroll service experiences downtime during a mass update?
  • If this system needs to scale to 10 million employees, what components would you move to asynchronous processing or caching?
  • How would you ensure that personal identifiable information (PII) is encrypted at rest and access is restricted according to the principle of least privilege?