This was the main question and it ate up most of the session.
Start by clarifying requirements and constraints (e.g., payout frequency, payment methods, scale) to scope the design. Then, walk through the core components: earnings calculation, payout scheduling, payment provider integration, and transaction history API, discussing trade-offs and data models. Finally, address scalability, reliability, and security considerations.
Pro tip: Emphasize idempotency and exactly-once processing in payment flows to prevent duplicate payouts, and discuss how to handle failures and retries gracefully.
Ask questions to understand expected scale, payout frequency (daily, weekly, instant), supported payment methods, and regulatory constraints. This ensures the design meets actual needs.
Define how driver earnings are computed from deliveries, including base pay, tips, bonuses, and deductions. Consider real-time vs. batch processing and how to handle adjustments.
Determine when and how payouts are triggered (e.g., scheduled cron jobs, event-driven). Discuss batching, cutoff times, and handling of pending earnings.
Choose payment providers (e.g., Stripe, PayPal) and design integration for initiating payouts, handling callbacks, and managing failures. Ensure idempotency and reconciliation.
Design RESTful endpoints for drivers to view earnings and payout history. Include pagination, filtering, and authentication. Consider data consistency and latency.
AI-generated suggestions, not part of the candidate's original notes. May be inaccurate — verify before relying on them.
The follow-up I was kind of dreading but also half-expected at a payments company.
Start by clarifying the requirements and constraints, then walk through the end-to-end flow of a payout, identifying failure points and designing a resilient retry mechanism with idempotency. Discuss how to handle different failure types, maintain accurate driver balances, and ensure transparency through communication.
Pro tip: Emphasize idempotency and reconciliation: use idempotency keys to prevent duplicate payouts and implement a reconciliation process to catch discrepancies. Also, consider the driver's perspective by providing clear status updates and expected resolution times.
Ask about payout frequency, provider SLAs, regulatory requirements, and driver expectations. Understand the scale and criticality of payouts.
Define retry logic with exponential backoff and jitter, set a maximum retry limit, and use idempotency keys to avoid duplicate payouts. Consider fallback providers if available.
Categorize failures (transient vs. permanent) and define states: pending, retrying, failed, and manual review. Ensure the system can recover and reconcile.
Communicate payout status through the driver app, including delays and expected resolution. Provide a clear timeline and support contact.
Implement monitoring and alerts for payout failures, and a reconciliation process to detect and correct discrepancies between internal ledger and provider records.
AI-generated suggestions, not part of the candidate's original notes. May be inaccurate — verify before relying on them.