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HubSpot·Software Engineer·Onsite - System Design / Architecture·Intermediate

Intermediate
Jul 2026

Summary

HubSpot system design round for a software engineer role. One question, pretty focused, and it pushed into some edge cases I hadn't fully thought through before sitting down.

Questions Asked (1)

Q1

Design a scheduled payments feature that executes transfers at a specified future time, updates account balances accordingly, and skips the transaction if the source account has insufficient funds at execution time.

System DesignTechnical Trade-offsData Modeling
Author's notes

The insufficient funds check tripped me up more than I expected.

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AI HintsAI Generated

Suggested Approach

Start by clarifying requirements and scale, then design a system with a scheduler that triggers payment execution, a transaction processor that checks balances and performs transfers atomically, and a data model that tracks scheduled payments and account balances. Discuss trade-offs around consistency, idempotency, and failure handling.

Pro tip: Emphasize idempotency and exactly-once execution: scheduled jobs can be retried, so ensure each payment is processed only once even if the scheduler fires multiple times. Also, consider using a database transaction with row-level locking to prevent race conditions on balance checks.

1. Clarify Requirements and Scale

Ask about expected volume, latency requirements, and whether payments can be cancelled or modified. Understand if the system needs to handle time zones and recurring payments.

2. High-Level Architecture

Propose a scheduler service that polls for due payments and enqueues them, and a payment processor that executes transfers. Consider using a distributed job scheduler like Quartz or a cloud service like AWS EventBridge.

3. Data Model and Storage

Design tables for scheduled_payments (id, source_account, destination_account, amount, scheduled_time, status) and accounts (id, balance). Use a relational database with ACID transactions for consistency.

4. Execution Flow and Concurrency

Describe how the processor locks the source account row, checks balance, and if sufficient, debits and credits atomically. If insufficient, mark payment as failed/skipped. Use idempotency keys to avoid double processing.

5. Failure Handling and Scalability

Discuss retries with exponential backoff, dead-letter queues for failed payments, and how to scale horizontally by partitioning payments. Mention monitoring and alerting for failed executions.

Key Points to Mention

  • Idempotency: ensure each scheduled payment is processed exactly once, even with retries.
  • Atomicity: use database transactions to update balances and payment status together.
  • Concurrency control: row-level locking or optimistic concurrency to prevent race conditions.
  • Scheduling mechanism: compare polling vs. event-driven triggers, and how to handle missed executions.
  • Failure modes: insufficient funds, network errors, and how to notify users.
  • Scalability: partitioning by time or account, and using a distributed queue for processing.

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