Contract
0–10
Write the main API or event contract and enumerate invalid or duplicate requests.
Evidence: Request, response, error, and idempotency semantics.
Who this is for
Backend engineers preparing for mid-level or senior coding and system design rounds where interviewers expect implementation detail as well as architecture.
Use the mock interview deliberately
What this practice should reveal
A useful backend mock interview follows a request across boundaries. Define the API contract, validate the state transition, choose the authoritative store, account for concurrent requests, and decide how callers learn whether the operation succeeded.
Do not stop at the happy path. Strong practice adds timeouts, retries, idempotency, queue pressure, schema evolution, security boundaries, metrics, and a plan for investigating a production incident without corrupting data.
Core capabilities
What to practice under pressure
1
API and domain contracts
Specify resources, commands, validation, error semantics, idempotency keys, pagination, and compatibility expectations.
2
Data ownership
Choose schemas and indexes from access patterns, then make transaction and consistency boundaries explicit.
3
Concurrency and queues
Reason about duplicate work, ordering, race conditions, backpressure, dead letters, and safe replay.
4
Operational reliability
Define SLOs, signals, dashboards, alerts, runbooks, and degraded behavior before the system is under stress.
Timed session
A 60-minute mock interview plan
PhaseTimeActivityEvidence to produce
State
10–25
Model the data lifecycle, indexes, transactions, and ownership boundaries.
Evidence: A schema tied directly to read and write paths.
Scale
25–43
Introduce caching, partitioning, queues, and concurrency controls only where estimates justify them.
Evidence: A bottleneck-led scaling sequence.
Operate
43–60
Walk through dependency failure, safe retries, observability, and incident recovery.
Evidence: A failure matrix with user-visible behavior.
Live practice
Run these interview scenarios
The scenarios are independent practice. Open the public prompt first, then run it in the matching workspace with voice follow-ups and evidence-based review.
Medium · system design
Design a Rate Limiter
Design a service to limit the number of requests a user can send to an API within a time window.
Hard · system design
Design a Payment System
Design a reliable payment processing backend like Stripe or PayPal. Focus on correctness and idempotency.
Hard · system design
Design Job Scheduler
Design a distributed job scheduler capable of handling recurring and one-time tasks at scale.
Hard · system design
Design a Distributed Message Queue
Design a high-throughput distributed message queue similar to Apache Kafka or RabbitMQ.
Self-review scorecard
Look for evidence, not confidence
Contracts
Strong signal: Defines stable semantics before implementation.
Warning signal: Treats an endpoint name as a complete API design.
Data
Strong signal: Derives schema and indexes from access patterns.
Warning signal: Selects a database by popularity.
Concurrency
Strong signal: Protects invariants under duplicates and races.
Warning signal: Assumes requests arrive once and in order.
Operations
Strong signal: Makes failures diagnosable and recovery safe.
Warning signal: Mentions monitoring without naming signals or actions.
Frequently asked questions
Backend Engineer Mock Interview FAQ
What is usually tested in a backend engineer interview?
Expect API and data modelling, coding fundamentals, distributed-systems trade-offs, concurrency, reliability, and the ability to debug a service through evidence.
Do I need to memorize database internals?
You need enough depth to defend indexes, transactions, partitioning, replication, and failure behavior. Memorizing product feature lists is less useful than tracing a real access path.
How should I answer an API design follow-up?
Start from the invariant and caller expectation, then discuss validation, idempotency, errors, compatibility, and observability before optimizing transport details.