Topic
System Design interview questions
1311 System Design questions from 230 companies, with hints, runnable code and solution walkthroughs.
60 easy819 medium432 hard
System Design interview questions by the numbers
Last updated
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
Most mentioned in interview experiences
- 1.Design delivery driver payment system3 reports
- 2.Debug round-robin request router2 reports
- 3.Design a basic bank system API2 reports
- 4.Design a delivery cost system2 reports
- 5.Design a Distributed Key-Value Store for a Small Company's Internal Use2 reports
- 6.Design a Donation System for a Three-Day Fundraising Campaign2 reports
- 7.Design a file search module like UNIX find2 reports
- 8.Design a Food Review System for a Delivery App, Focused on the Database Schema2 reports
- 9.Design a Job Scheduler for ML Training and Batch Inference on a Shared Cluster2 reports
- 10.Design a Menu Item Review and Rating System for a Food-Delivery Platform2 reports
Counted from 393 candidate interview experiences on Katkat. How we collect and count
Showing 391–420 of 1311 results
This question evaluates system design competencies such as API design, data modeling and storage selection for aggregated 5-point ratings, handling user-generated posts and likes, service decomposition, consistency trade-offs, scalability, and designing a monthly batch payout pipeline for driver earnings.
DoorDashSoftware EngineerSystem DesignOnsiteDesign item reviews and votes with purchase eligibility, unique reviews, rating aggregates, reliable counters, pagination, and recoverable caching.
DoorDashSoftware EngineerSystem DesignOnsiteThis question evaluates competence in designing scalable, fault-tolerant streaming systems and implementing correct time-windowed aggregation logic, testing skills in distributed systems, stream processing, and data correctness; it belongs to the system design domain and streaming/real-time data engineering and spans both conceptual architectural thinking and practical application-level concerns. It is commonly asked to probe reasoning about correctness under at-least-once delivery and messy inputs (out-of-order, duplicate, late, or malformed events), operational resilience, and trade-offs between throughput, latency, and auditability in production-scale pipelines.
DoorDashSoftware EngineerSystem DesignTechnical ScreenThis question evaluates competency in designing scalable, highly available payment-enabled distributed systems, including skills in traffic spike handling, idempotency and reconciliation, real-time totals and leaderboards, latency and throughput planning, and compliance/privacy considerations.
DoorDashSoftware EngineerSystem DesignOnsiteThis question tests the ability to design a scalable review system capable of handling high-write volume, media storage, and efficient retrieval with pagination.
DoorDashSoftware EngineerSystem DesignTechnical ScreenDesign donation collection and charity payouts with a PSP, idempotent state transitions, durable ledger records, asynchronous provider events, and reconciliation.
DoorDashSoftware EngineerSystem DesignOnsiteDesign a donation system for a fundraising campaign that runs for exactly three days, where donors choose a charity, pay through a payment processor and see running totals. It tests payment idempotency and reconciliation, handling a time-boxed traffic burst, avoiding write hotspots on totals, and fraud protection.
DoorDashSoftware EngineerSystem DesignOnsiteA DoorDash system design prompt to build a food item review system for a delivery app that also rewards customers for reviewing. It tests product judgment on open questions, verified-purchase writes, cached rating aggregates, and designing a practical, abuse-resistant reward program with reliable crediting.
DoorDashSoftware EngineerSystem DesignOnsiteThis problem tests your ability to design a distributed, read-heavy rating and review system that handles high concurrency and ensures data integrity.
DoorDashSoftware EngineerSystem DesignOnsiteDesign a food review platform for discovery, ratings, review text, optional dish-level content, and trusted aggregates. Define entity and review contracts, search and read paths, moderation, abuse resistance, privacy, scaling, and operational recovery.
DoorDashSoftware EngineerSystem DesignOnsiteSystem design question for the review feature of a food-delivery platform, where customers rate and review the food from delivered orders and others browse ratings. The focus is database schema design: tables, keys, constraints, indexes, rating aggregates, and how edits, deletes and moderation keep them correct.
DoorDashSoftware EngineerSystem DesignOnsiteDesign a scalable review and voting platform for dishes and restaurants, focusing on transactional vote changes, aggregate counter consistency, hot-item read/write scaling, and stable pagination.
DoorDashSoftware EngineerSystem DesignOnsiteDesign an item-level review and rating platform for food delivery that handles high-throughput reads, asynchronous sentiment and moderation pipelines, and near real-time score aggregations.
DoorDashSoftware EngineerSystem DesignOnsiteA system design question on a menu review feature for a food-delivery platform, where customers rate and review the menu items they ordered. It tests requirement prioritization, detailed review schema and API design, rating aggregation, caching and moderation, and time management that still reaches a deep dive.
DoorDashSoftware EngineerSystem DesignOnsiteDesign a resilient, distributed workflow orchestration engine capable of executing multi-step business processes across heterogeneous services with strict guarantees around durability, idempotency, and failure recovery.
DoorDashSoftware EngineerSystem DesignOnsiteThis problem tests your ability to design a high-throughput observability pipeline capable of ingesting, storing, and alerting on time-series metrics from a distributed fleet of services.
DoorDashSoftware EngineerSystem DesignOnsiteDesign a resilient, stateful workflow orchestration engine to process complex order refunds as a Directed Acyclic Graph (DAG), ensuring idempotency, crash recovery, and financial consistency.
DoorDashSoftware EngineerSystem DesignOnsiteDesign a review and rating system for a food-delivery platform, where customers review the individual menu items they received and every menu shows each item's rating. It tests data modeling, purchase verification, incremental rating aggregation, caching for read-heavy menus, moderation, and handling bursts on popular items.
DoorDashSoftware EngineerSystem DesignOnsiteThis problem tests the ability to design a high-throughput, real-time analytics system that maintains a top-k leaderboard over a sliding time window.
DoorDashSoftware EngineerSystem DesignOnsiteDesign a distributed cron job scheduler evaluates requirements, scale assumptions, API/data design, architecture, trade-offs, failure modes, and rollout in a realistic interview setting. A strong answer states assumptions, handles edge cases, explains trade-offs, and shows how to validate the result clearly.
DoorDashSoftware EngineerSystem DesignOnsiteThis question evaluates a candidate's competency in designing scalable, low-latency streaming data systems, covering event-time windowing, rolling-window aggregation, idempotency for duplicate events, late/out-of-order handling, and auditability.
DoorDashSoftware EngineerSystem DesignOnsiteThis System Design question evaluates distributed-systems and API-design skills—scalability, reliable fanout, multi-channel integration, delivery guarantees (retries, idempotency, deduplication), rate-limiting, subscription/preferences modeling, and observability.
DoorDashSoftware EngineerSystem DesignOnline AssessmentThis question evaluates a candidate's competency in designing scalable, reliable multi-channel notification platforms, covering distributed systems, multitenancy, API and storage schema design, queuing and retry strategies, rate limiting, observability, localization, A/B testing, and compliance considerations like GDPR.
DoorDashSoftware EngineerSystem DesignTechnical ScreenThis question evaluates skills in resilient API aggregation, fault-tolerant microservice orchestration, and reliability engineering, focusing on defining API contract semantics and handling partial failures at the architectural/system-design level (service-to-service abstraction); category/domain: System Design.
DoorDashSoftware EngineerSystem DesignTechnical ScreenA DoorDash software-engineer system-design interview question: design a resilient Dasher payment system that computes payouts from order lifecycle events (accept/fulfill/cancel). It spans event-driven ingestion, idempotency and exactly-once-vs-at-least-once semantics, data modeling for high write throughput and per-dasher pay-period queries, timezone/DST handling, detection and remediation of missing or out-of-order data, batch-vs-streaming reconciliation, reliability, and consistency trade-offs.
DoorDashSoftware EngineerSystem DesignTechnical ScreenDesign a scalable Instagram-like platform evaluates requirements, scale assumptions, API/data design, architecture, trade-offs, failure modes, and rollout in a realistic interview setting. A strong answer states assumptions, handles edge cases, explains trade-offs, and shows how to validate the result clearly.
DoorDashSoftware EngineerSystem DesignTechnical ScreenThis question evaluates an engineer's ability to design scalable, low-latency, and resilient online recommendation serving infrastructure, emphasizing caching strategies, partitioning/sharding, data storage consistency, and observability.
DoorDashMachine Learning EngineerSystem DesignOnsiteDesign a service aggregator with robust error handling evaluates requirements, scale assumptions, API/data design, architecture, trade-offs, failure modes, and rollout in a realistic interview setting. A strong answer states assumptions, handles edge cases, explains trade-offs, and shows how to validate the result clearly.
DoorDashSoftware EngineerSystem DesignTechnical ScreenDesign a reliable, scalable alert and event notification delivery platform that decouples upstream producers from heterogeneous downstream consumers with independent fan-out, isolation, retries, and dead-letter handling.
DoorDashSoftware EngineerSystem DesignTechnical ScreenDesign the review and rating feature of an online course marketplace where only learners who completed a course may rate it, with the discussion centered on table design, keys, constraints, and the indexes each read path needs.
DoorDashSoftware EngineerSystem DesignOnsite