Start by clarifying requirements and scale, then design a data model and API for core operations (create, deposit, transfer). For advanced features like top spenders, cashback, and payment status, discuss appropriate data structures (e.g., heaps, indexes) and consistency guarantees, emphasizing idempotency and transactional integrity.
Pro tip: Demonstrate awareness of financial system constraints: highlight idempotency keys for transfers and payments, and discuss how to handle race conditions in concurrent balance updates using optimistic locking or serializable transactions.
Ask about expected throughput, consistency needs, and whether the system is for internal or external use. Clarify if top spenders are global or per time window, and cashback rules.
Define entities: Account (id, balance, owner), Transaction (id, from, to, amount, status, timestamp), Payment (id, account, amount, cashback, status). Choose a relational DB for ACID or NoSQL for scale, and discuss indexing for queries.
Outline RESTful endpoints: POST /accounts, POST /accounts/{id}/deposit, POST /transfers, GET /accounts/top-spenders, POST /payments, GET /payments/{id}. Specify request/response schemas and idempotency keys.
For top spenders, use a sorted set or maintain a leaderboard with periodic updates. For cashback, calculate on payment success and credit asynchronously. For payment status, use a state machine (pending, completed, failed) with webhooks or polling.
Explain how to ensure atomic transfers (e.g., two-phase commit or sagas), handle idempotency, and scale reads with replicas. Discuss trade-offs between strong and eventual consistency for top spenders.
AI-generated suggestions, not part of the candidate's original notes. May be inaccurate — verify before relying on them.