System Design interview questions

Showing 1051–1080 of 1311 results

• Design a hotel search and booking systemHard

  This question tests the ability to design a distributed, high-concurrency reservation system that handles inventory management, consistency, and search efficiency.

  RipplingSoftware EngineerSystem DesignOnsite
• Design a large-scale news app with cachingMedium

  This question evaluates a candidate's ability to design a scalable news application with emphasis on caching strategies and cross-device read-state synchronization, assessing skills in system architecture, API design, data modeling, distributed caching, and consistency handling.

  RipplingSoftware EngineerSystem DesignOnsite
• Design a news aggregation and feed serviceHard

  This question tests the ability to design a distributed system capable of ingesting high-frequency news feeds from multiple sources and serving personalized, low-latency content to millions of users.

  RipplingSoftware EngineerSystem DesignOnsite
• Design a news aggregator like Google NewsMedium

  This problem tests your ability to design a distributed system that fetches, normalizes, and ranks news articles from various heterogeneous sources while maintaining high availability and low latency for users.

  RipplingSoftware EngineerSystem DesignTechnical Screen
• Design a personalized news aggregatorMedium

  This question evaluates a candidate's competence in large-scale system design, covering concepts such as high-throughput API ingestion, idempotent processing and deduplication, indexing and storage, caching, and low-latency personalized feed generation.

  RipplingSoftware EngineerSystem DesignOnsite
• Design a real-time delivery dashboardHard

  This question evaluates skills in designing scalable, low-latency real-time distributed systems—covering event ingestion and streaming, geospatial indexing, state management, consistency and availability trade-offs, fault tolerance, monitoring, and cost/performance considerations—and is categorized under System Design.

  RipplingSoftware EngineerSystem DesignTechnical Screen
• Design a scalable expense rules engineHard

  This question evaluates system-design and data-modeling competency for building a scalable, multi-tenant rules engine (category: System Design) that supports per-entity and aggregate (trip-level) evaluations, backward-compatible APIs, explainability/auditability, parsing/validation of string-typed inputs, and operational concerns like determinism, idempotency, and resilience. It is commonly asked to assess trade-off reasoning around extensibility, evaluation semantics (priority, combinators, short-circuiting), aggregation and caching strategies, and API/data-model stability, with a level of abstraction that is practical application focused while requiring conceptual architectural trade-offs and concrete design details.

  RipplingSoftware EngineerSystem DesignTechnical Screen
• Design a scalable logging systemMedium

  This question evaluates a candidate's ability to design scalable, reliable logging and observability infrastructure, testing competencies in distributed systems, ingestion pipelines, indexing and data modeling, storage and retention policies, multi-tenancy, and performance/reliability trade-offs.

  RipplingSoftware EngineerSystem DesignOnsite
• Design a user behavior monitoring systemMedium

  This question evaluates a candidate's ability to design scalable, low-latency user event ingestion and analytics pipelines while reasoning about data storage choices and aggregate correctness trade-offs.

  RipplingSoftware EngineerSystem DesignOnsite
• Design a user behavior tracking systemHard

  This question evaluates competency in designing scalable event-driven systems, covering client SDKs and server ingestion, buffering and delivery guarantees, schema evolution, storage trade-offs for interactive dashboards versus large-scale warehousing, enrichment placement, and privacy/compliance controls.

  RipplingSoftware EngineerSystem DesignTechnical Screen
• Design an ad-click aggregation and enrichment pipelineMedium

  This question evaluates system design and data engineering competencies, focusing on large-scale streaming ingestion, aggregation, enrichment joins, deduplication, and trade-offs between request batching and latency for mobile networks.

  RipplingSoftware EngineerSystem DesignOnsite
• Design centralized log ingestion and query systemMedium

  This problem tests your ability to design a distributed log processing pipeline capable of handling high-throughput ingestion and efficient time-range retrieval.

  RipplingSoftware EngineerSystem DesignTechnical Screen
• Design delivery driver payment systemMedium

  A Rippling software-engineer system-design screen: build an in-memory, object-oriented driver-payroll service with add_driver, record_delivery, get_total_cost, pay_up_to, and get_total_cost_unpaid. It tests time-interval accounting, integer-cents money math, idempotent partial-vs-whole payout state, double-pay prevention for overlapping work, and a clean path from prototype to a transactional, indexed production design.

  RipplingSoftware EngineerSystem DesignTechnical Screen
• Design in-memory delivery billing core APIsMedium

  This problem tests your ability to design an efficient in-memory service for managing delivery billing, requiring careful consideration of concurrency, precision in monetary calculations, and optimized aggregation of billable events.

  RipplingSoftware EngineerSystem DesignOnsite
• Design personalized news aggregation serviceMedium

  This question tests the ability to design a scalable news aggregation system that balances real-time content ingestion with personalized ranking for a large user base.

  RipplingSoftware EngineerSystem DesignTechnical Screen
• Design several large-scale systemsHard

  This question tests the ability to design a distributed, high-concurrency reservation system that requires strong consistency for inventory management and low-latency read access for search.

  RipplingSoftware EngineerSystem DesignHR Screen
• Extend rules for trip-level aggregates and outputsMedium

  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 Extend rules for trip-level aggregates and outputs states assumptions, handles edge cases, explains trade-offs, and shows how to validate the result clearly.

  RipplingSoftware EngineerSystem DesignTechnical Screen
• How would you scale rule evaluation?Easy

  This question tests your ability to design a high-throughput, rule-based processing engine that balances performance, scalability, and maintainability under high load.

  RipplingSoftware EngineerSystem DesignTechnical Screen
• Prevent Duplicate Payments Under High LoadMedium

  Design a highly reliable payment processing system that guarantees exactly-once execution and prevents duplicate charges during high-concurrency spikes and downstream failure scenarios.

  RipplingSoftware EngineerSystem DesignOnsite
• Design and Debug an Automotive Sensor and Camera-Blockage SystemMedium

  Tests your ability to design an automotive perception sensor layout and lens-blockage detection system, define safe vehicle degradation strategies, and systematically troubleshoot intermittent false-positive diagnostic alerts in the field.

  RivianSoftware EngineerSystem DesignTechnical Screen
• Design Payment Processing with Idempotency and ReconciliationMedium

  Design a resilient payment processing system that interfaces with third-party payment gateways, guarantees exactly-once execution via idempotency, manages complex payment state machines, and resolves discrepancies via reconciliation.

  RobinhoodSoftware EngineerSystem DesignOnsite
• Design a Cron Job Scheduler for 100K Jobs With At-Least-Once ExecutionMedium

  A system design question about a cron job scheduler that stores about 100,000 recurring job definitions, runs up to 10,000 jobs at once and guarantees at-least-once execution. It tests data modeling, including whether a schedule belongs on the job, finding and dispatching due jobs at scale, and failure handling with leases and retries.

  RobinhoodSoftware EngineerSystem DesignOnsite
• Design a Distributed Scheduler with At-Most-Once RunsHard

  Design a distributed scheduler around strict at-most-once run starts, durable identities, ambiguous crashes, SLA failures, queue recovery, logs, and notification outboxes.

  RobinhoodSoftware EngineerSystem DesignOnsite
• Design a Fault-Tolerant Distributed Job SchedulerMedium

  This question tests the ability to design a distributed, fault-tolerant system capable of scheduling and executing tasks reliably at scale, emphasizing durability, state management, and consistency.

  RobinhoodSoftware EngineerSystem DesignOnsite
• Design a Photo Album AppMedium

  This question evaluates proficiency in frontend system design, specifically client-side component and data architecture, state management and normalization, real-time synchronization, and large-media upload flows; it sits in the System Design domain with a Frontend Engineer focus and tests practical application of these competencies.

  RobinhoodFrontend EngineerSystem DesignOnsite
• Design a Photo Management ServiceMedium

  This question evaluates a candidate's ability to design scalable, reliable photo management systems, focusing on API design, storage architecture, metadata modeling, album management, and operational concerns for large numbers of users and photos.

  RobinhoodSoftware EngineerSystem DesignOnsite
• Design a Reliable Distributed Job SchedulerMedium

  This question tests the ability to design a distributed, fault-tolerant job scheduler capable of handling job lifecycle states, worker coordination, and consistent scheduling across multiple tenants.

  RobinhoodSoftware EngineerSystem DesignTechnical Screen
• Design a Task Scheduler and ExecutorMedium

  Design a high-scale task scheduler for one-time, cron-like, fixed-rate, and fixed-delay execution. Cover versioned task and attempt states, due-time indexing, safe concurrent claims, retries, leases, backpressure, idempotency, recurrence semantics, and recovery.

  RobinhoodSoftware EngineerSystem DesignOnsite
• Design a distributed job schedulerMedium

  This question tests the ability to design a fault-tolerant, scalable distributed system capable of scheduling one-time and recurring background tasks with guaranteed execution semantics.

  RobinhoodSoftware EngineerSystem DesignOnsite
• Design a distributed job scheduler serviceEasy

  This question evaluates understanding of distributed systems and microservice architecture, scheduling and timeout semantics, fault tolerance, scalability, and data modeling for job metadata, run history, and logs.

  RobinhoodSoftware EngineerSystem DesignTechnical Screen