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Airbnb·Software Engineer·Technical Phone Screen·Intermediate

Intermediate
May 2026

Summary

Airbnb software engineer interview with a classic OOP design question. Nothing flashy, but the scope creep potential is real if you're not careful about what you actually need to implement.

Questions Asked (1)

Q1

Design and implement a banking system that supports depositing funds, withdrawing funds, transferring money between accounts, and checking an account balance.

System DesignAlgorithms & Data StructuresTechnical Trade-offs
Author's notes

Spent the first few minutes just clarifying scope because 'banking system' could mean a lot of things.

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AI HintsAI Generated

Suggested Approach

Start by clarifying requirements and constraints, then design a high-level architecture that separates concerns (e.g., API layer, service layer, data layer). Focus on core operations (deposit, withdraw, transfer, balance) and discuss data consistency, concurrency, and scalability trade-offs.

Pro tip: Demonstrate awareness of real-world banking constraints like ACID transactions and idempotency, and proactively discuss how you'd handle failures and ensure data integrity.

1. Clarify Requirements

Ask questions to understand scope: expected scale (users, transactions per second), consistency requirements (strong vs eventual), and whether this is a single-node or distributed system.

2. Define Core Data Model

Outline the main entities (Account, Transaction) and their attributes (account ID, balance, transaction ID, timestamp, status). Consider using a ledger-based approach for auditability.

3. Design API and Service Layer

Define RESTful endpoints or RPC methods for deposit, withdraw, transfer, and getBalance. Describe how the service layer orchestrates operations, validates inputs, and enforces business rules.

4. Address Concurrency and Consistency

Explain how to handle concurrent operations (e.g., locking, optimistic concurrency, or serializable transactions) to prevent race conditions and ensure balance accuracy.

5. Discuss Scalability and Trade-offs

Talk about scaling reads/writes (e.g., sharding by account ID, caching balances), and trade-offs between consistency, availability, and latency (CAP theorem).

Key Points to Mention

  • ACID transactions and isolation levels to ensure atomicity and consistency for transfers.
  • Idempotency keys to prevent duplicate operations (e.g., double deposits).
  • Concurrency control mechanisms: pessimistic vs optimistic locking, or serializable transactions.
  • Data partitioning/sharding strategies to scale horizontally (e.g., by account ID).
  • Audit trail and ledger design for traceability and reconciliation.
  • Failure handling: retries, dead-letter queues, and compensating transactions (Saga pattern) for distributed transactions.

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