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

SeniorPrefer not to say

Apr 2026

Summary

System design round at Confluent for a software engineer role. The whole thing was focused on designing a disposable email service at scale, which sounds simple enough until you're 20 minutes in and realizing you forgot to think about SMTP ingestion at all.

Questions Asked (1)

Design a disposable/temporary email service that can support 100 million active users.

System DesignTechnical Trade-offsData Modeling

Author's notes

I started with address generation and inbox reads, which felt natural, but the interviewer kept nudging me toward the write path.

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AI HintsAI Generated

Suggested Approach

Start by clarifying requirements and scale, then design a high-level architecture focusing on core components like email ingestion, storage, and retrieval. Dive into data modeling and trade-offs for handling 100M users, emphasizing scalability and cost-efficiency.

Pro tip: Highlight the importance of email deliverability and anti-abuse measures, as these are often overlooked but critical for a temporary email service at scale.

1. Clarify Requirements

Ask questions to understand functional and non-functional requirements, such as email retention period, expected email volume, and security needs.

2. High-Level Design

Outline the main components: email receiving (SMTP servers), storage (database and object storage), and user interface (web/API).

3. Data Modeling

Design schemas for users, email addresses, and messages, considering partitioning and indexing for fast access and cleanup.

4. Scalability and Trade-offs

Discuss scaling strategies like sharding, caching, and using cloud services, and trade-offs between consistency, availability, and cost.

5. Address Challenges

Cover anti-abuse, email deliverability, and data retention policies, and how to handle spikes in traffic.

Key Points to Mention

Use of cloud services (e.g., AWS SES, S3) for scalability and cost-efficiency
Data partitioning and sharding strategies for user and email data
Caching mechanisms (e.g., Redis) for frequently accessed emails
Anti-abuse measures like rate limiting and CAPTCHA
Email retention and automatic deletion policies
Monitoring and alerting for system health and performance

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