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System Design interview questions

1311 System Design questions from 230 companies, with hints, runnable code and solution walkthroughs.

Questions1311

60 easy819 medium432 hard

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System Design interview questions by the numbers

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Katkat has 1,311 System Design interview questions from 230 companies; the most come from OpenAI (8%), Meta (5%) and Amazon (4%). By difficulty: 5% easy, 62% medium and 33% hard. The most common round is Onsite (55%). Frequent concepts include System Design, Distributed Systems, Scalability and Caching.

Companies (230)

Difficulty

  • Easy5% · 60
  • Medium62% · 819
  • Hard33% · 432

Interview rounds

  • Onsite55% · 721
  • Technical Screen39% · 517
  • Online Assessment3% · 38
  • Other2% · 21
  • HR Screen1% · 13

Roles

  • Software Engineer91% · 1189
  • Machine Learning Engineer2% · 31
  • Data Engineer2% · 26
  • Backend Engineer2% · 25
  • Frontend Engineer1% · 19

Frequent concepts

  • System Design31% · 400
  • Distributed Systems24% · 316
  • Scalability15% · 196
  • Caching7% · 95
  • Concurrency7% · 91
  • system-design6% · 83

Showing 421–450 of 1311 results

  • This question evaluates a candidate's ability to design scalable, reliable payment systems and asynchronous processing pipelines, covering competencies in distributed systems, idempotency, data modeling, security/PCI compliance, retry and dead-letter strategies, and observability.

    DoorDashSoftware EngineerSystem DesignOnsite
  • This question evaluates understanding of consistent hashing, replica placement, dynamic membership, weighted load distribution, rebalancing impact, and related distributed-systems competencies for routing and sharding.

    DoorDashSoftware EngineerSystem DesignOnsite
  • This interview question evaluates requirements, scale assumptions, API/data design, architecture, trade-offs, failure modes, and rollout in a realistic interview setting. A strong answer for Design consistent hashing with a sorted map states assumptions, handles edge cases, explains trade-offs, and shows how to validate the result clearly.

    DoorDashSoftware EngineerSystem DesignTechnical Screen
  • This interview question evaluates requirements, scale assumptions, API/data design, architecture, trade-offs, failure modes, and rollout in a realistic interview setting. A strong answer for Design limited-time donation platform states assumptions, handles edge cases, explains trade-offs, and shows how to validate the result clearly.

    DoorDashSoftware EngineerSystem DesignTechnical Screen
  • This interview question evaluates requirements, scale assumptions, API/data design, architecture, trade-offs, failure modes, and rollout in a realistic interview setting. A strong answer for Design notification and project architecture states assumptions, handles edge cases, explains trade-offs, and shows how to validate the result clearly.

    DoorDashSoftware EngineerSystem DesignTechnical Screen
  • This question tests the ability to design an end-to-end personalized restaurant recommendation system, covering feature engineering, retrieval-ranking architecture, and infrastructure trade-offs.

    DoorDashMachine Learning EngineerSystem DesignTechnical Screen
  • This system design question evaluates a candidate's ability to architect a scalable review platform with voting, counter aggregation, and rewards at high traffic volumes. It tests practical knowledge of distributed counter strategies, idempotent write handling, read/write path separation, and abuse prevention — core competencies assessed in senior software engineer interviews.

    DoorDashSoftware EngineerSystem DesignOnsite
  • Explain how a Dasher pay calculation driven by upstream order records stays correct when those records contain duplicates. Tests deciding when two records describe the same fact, making processing safe against replayed records, handling conflicting and late data or corrections after payout, and preventing double payouts.

    DoorDashSoftware EngineerSystem DesignTechnical Screen
  • A system design follow-up about paying delivery drivers when the downstream payment service is unavailable. It tests reasoning about timeouts with unknown outcomes, durable records of amounts owed, retries that must never double-pay, recovery after long outages, reconciliation, and what drivers and operators see while payouts are delayed.

    DoorDashSoftware EngineerSystem DesignTechnical Screen
  • Design order DAG execution with prerequisite state, atomic completion-versus-timeout decisions, idempotent refunds, durable recovery, and accurate status queries.

    DoorDashSoftware EngineerSystem DesignOnsite
  • This question evaluates system design competencies in service reliability and storage architecture, focusing on SLA protection during upstream latency spikes and trade-offs in choosing in-memory caches (e.g., Redis), relational databases, or alternative storage for order and payment state.

    DoorDashSoftware EngineerSystem DesignTechnical Screen
  • This question evaluates a candidate's ability to design and scale a distributed caching system, testing competencies in sharding and consistent hashing, replication and consistency models, request routing, failure detection, cache invalidation, capacity planning, and operational trade-offs for high-throughput, low-latency workloads.

    DoorDashSoftware EngineerSystem DesignTechnical Screen
  • This prompt evaluates expertise in distributed systems, asynchronous task orchestration, recursive job scheduling, data modeling for job and file metadata, and reliability concerns such as retries, idempotency, deduplication, and partial failure handling.

    DropboxSoftware EngineerSystem DesignOnsite
  • This problem evaluates your ability to design a distributed, highly available, and scalable object storage system capable of handling massive volumes of unstructured data.

    DropboxSoftware EngineerSystem DesignOnsite
  • This question evaluates a candidate's ability to design HTTP APIs and scalable backend architectures for long-running file-processing jobs, covering competencies in API design, job orchestration, distributed systems, fault tolerance, state persistence, and idempotency.

    DropboxSoftware EngineerSystem DesignOnsite
  • This question tests the ability to design an asynchronous distributed system for crawling large file structures, focusing on job orchestration, state management, and scalability under high-latency operations.

    DropboxSoftware EngineerSystem DesignTechnical Screen
  • This interview question evaluates requirements, scale assumptions, API/data design, architecture, trade-offs, failure modes, and rollout in a realistic interview setting. A strong answer for Design Animal Chess game classes states assumptions, handles edge cases, explains trade-offs, and shows how to validate the result clearly.

    DuolingoSoftware EngineerSystem DesignTechnical Screen
  • Design a pipeline that ingests a weather forecast CSV published daily at a variable time, validates and stores it, runs black-box demand, wind, solar, hydro and price models across every scenario, and serves aggregated forecasts to traders. It tests scheduling, DAG design, failure handling, dashboard delivery and scaling to thousands of scenarios.

    EngelhartSoftware EngineerSystem DesignTechnical Screen
  • This problem tests your ability to design a robust middleware layer that abstracts heterogeneous downstream APIs into a unified, reliable, and performant service.

    ExpediaSoftware EngineerSystem DesignOnsite
  • This question evaluates a candidate's ability to design scalable, reliable REST APIs and distributed ingestion pipelines, testing competencies in API specification, idempotency, authentication/authorization, asynchronous processing, observability, and integration with downstream validation services.

    ExpediaSoftware EngineerSystem DesignTechnical Screen
  • This problem tests your ability to design a high-throughput, geo-aware notification system that must deliver time-sensitive alerts to users based on their current or planned location during natural disasters.

    ExpediaSoftware EngineerSystem DesignOnsite
  • This question tests the ability to design a scalable hierarchical data structure, select appropriate storage backends for recursive queries, and handle write-heavy concurrent updates to organizational charts.

    ExpediaSoftware EngineerSystem DesignOnsite
  • Design the backend for product likes on a marketplace where retailers like or dislike products, list the products they liked and see like counts in search results, while brands see the likes on their own products. Tests data modeling for two access directions, counter maintenance, idempotent writes and scaling the search read path.

    FaireSoftware EngineerSystem DesignOnsite
  • This question evaluates a candidate's competencies in designing scalable, low-latency retail trading systems, covering system architecture, order routing and state management, market data ingestion, cash and position ledger consistency, risk controls, and compliance/observability.

    FanaticsSoftware EngineerSystem DesignOnsite
  • Design a real-time, durable commenting system for an infinite collaborative whiteboard where comments attach to dynamic canvas objects or fixed coordinates.

    FigmaSoftware EngineerSystem DesignTechnical Screen
  • Design a permission-aware search and retrieval system for collaborative design files and assets that enforces hierarchical access control, supports hybrid search, and prevents data leakage.

    FigmaSoftware EngineerSystem DesignOnsite
  • Prepare for a real-time collaborative comments system design prompt for shared documents or canvases. The question covers durable comment writes, WebSocket fanout, reconnect backfill, ordering, permissions, hot-document scaling, and missed-update recovery.

    FigmaSoftware EngineerSystem DesignTechnical Screen
  • This problem tests the ability to design a distributed streaming architecture that aggregates real-time user activity while maintaining strict privacy and performance requirements.

    FigmaSoftware EngineerSystem DesignTechnical Screen
  • This question evaluates system design competence for building large-scale, near-real-time trending and feed systems, testing skills in streaming ingestion, event modeling, ranking algorithms, caching, consistency and fault-tolerance, capacity planning, and operational observability within the System Design domain.

    FigmaSoftware EngineerSystem DesignOnsite
  • This question evaluates a candidate's ability to design reliable, fault-tolerant asynchronous job scheduling systems, covering concepts such as immediate versus delayed execution, failure handling, retries, duplicate execution prevention, worker crashes, scheduler failover, and the feasibility of exactly-once semantics.

    FigmaSoftware EngineerSystem DesignOnsite

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