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

Senior

Jun 2026

Summary

Meta system design round for a software engineering role. The whole session was basically one big design problem about building an in-memory bank from scratch, and they went pretty deep on data structures and complexity guarantees.

Questions Asked (1)

Design an in-memory banking system supporting account creation, deposits, withdrawals, a top spenders query, scheduled payments with cancellation, and a process() function that executes due payments in order. Discuss data structures, time complexity targets, and how you'd test correctness and handle edge cases like duplicate scheduling or partial failures.

System DesignAlgorithms & Data StructuresTechnical Trade-offs

Author's notes

This one sprawled in every direction.

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AI HintsAI Generated

Suggested Approach

Start by clarifying requirements and constraints, then propose a modular design with clear data structures and algorithms, emphasizing time complexity and correctness. Walk through each operation, discussing trade-offs and edge cases, and conclude with a testing strategy.

Pro tip: Demonstrate awareness of concurrency and idempotency: even in an in-memory system, consider thread-safety and how to handle duplicate scheduling or partial failures gracefully.

1. Clarify Requirements and Constraints

Ask about expected scale, concurrency, persistence, and exact semantics of operations like top spenders and scheduled payments. Confirm whether process() should be atomic and how to handle failures.

2. Design Data Structures and Algorithms

Propose using hash maps for accounts, a min-heap for scheduled payments, and a balanced BST or sorted list for top spenders. Discuss time complexity for each operation.

3. Detail Operations and Edge Cases

Explain account creation, deposit, withdrawal, top spenders query, schedule/cancel payment, and process(). Address duplicate scheduling, insufficient funds, and partial failures.

4. Discuss Trade-offs and Optimizations

Compare alternative data structures (e.g., heap vs. sorted list for top spenders) and discuss trade-offs in time/space complexity, concurrency, and fault tolerance.

5. Outline Testing Strategy

Describe unit tests for each operation, integration tests for process(), and edge cases like duplicate IDs, concurrent modifications, and failure recovery.

Key Points to Mention

Use of hash map for O(1) account lookup and updates.
Min-heap for scheduled payments to efficiently retrieve due payments in O(log n).
Top spenders query: maintain a max-heap or sorted structure for O(1) or O(log n) retrieval.
Handling duplicate scheduling via unique payment IDs and idempotent operations.
Partial failures: ensure atomicity of process() or implement rollback/retry mechanisms.
Concurrency: use locks or concurrent data structures to ensure thread-safety.

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