Carvana·Software Engineer·Onsite - System Design / Architecture·Senior

Senior

Jun 2026

Summary

System design round at Carvana for a software engineering role. The whole thing was one big question about an employee attendance backend, and they really wanted to dig into every layer of it.

Questions Asked (1)

Design the backend service for an employee attendance system that handles clock-in/clock-out, pay period calculations, wage-based pay computation, high traffic at peak times, and syncing data from an external system. Walk through APIs, data model, architecture, consistency, failure handling, and scalability.

System DesignAPI & IntegrationsData Modeling

Author's notes

This is a lot of surface area for one question.

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AI HintsAI Generated

Suggested Approach

Start by clarifying requirements and scale, then propose a high-level architecture that separates write-heavy clock events from read-heavy payroll calculations. Walk through the data model, APIs, and how you handle peak traffic, external sync, and consistency. Finally, discuss trade-offs and failure scenarios to show depth.

Pro tip: Emphasize idempotency and exactly-once processing for clock events and external sync, as duplicate or missing punches directly impact pay and employee trust. Also, mention that you would use a write-optimized store for clock events and a read-optimized store for payroll queries to handle peak load.

1. Clarify Requirements and Scale

Ask about expected number of employees, peak clock-in/out times, pay period frequency, external system details, and consistency requirements. Establish functional and non-functional requirements.

2. Design Data Model and APIs

Define core entities like Employee, ClockEvent, PayPeriod, and Wage. Outline REST or gRPC APIs for clock-in/out, fetching attendance, and calculating pay. Ensure APIs are idempotent and support bulk operations.

3. Propose High-Level Architecture

Sketch components: API gateway, clock service, payroll service, external sync service, and data stores. Choose technologies (e.g., Kafka for events, Cassandra for writes, PostgreSQL for payroll) and explain data flow.

4. Address Consistency, Failure Handling, and Scalability

Discuss consistency models (e.g., eventual for sync, strong for pay), idempotency, retries, dead-letter queues, and how to scale horizontally during peaks. Mention monitoring and alerting.

5. Summarize Trade-offs and Future Improvements

Highlight key trade-offs (e.g., latency vs. consistency) and suggest potential enhancements like caching, sharding, or using a time-series database for clock events.

Key Points to Mention

Idempotent APIs for clock-in/out to handle duplicate requests and network retries.
Use of event sourcing or append-only log for clock events to ensure auditability and replayability.
Separation of write-heavy clock events (e.g., Cassandra) and read-heavy payroll queries (e.g., PostgreSQL with read replicas).
Handling peak traffic with auto-scaling, load balancing, and asynchronous processing via message queues.
External system sync using change data capture (CDC) or scheduled batch jobs with conflict resolution and idempotency.
Payroll calculation as a batch job that reads clock events, applies wage rules, and stores results with strong consistency.

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