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Interview Questions
Practice 9403 coding, system design and machine learning questions from 546 companies, sorted by role, topic and interview round. Every question has step-by-step hints, a code runner that supports 8 languages and an AI mentor; members also get the full solution walkthrough.
- 9403
- Questions
- 546
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- 11
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- 8
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Showing 1411–1440 of 4616 results
- DoorDashHardSoftware EngineerCount changed nodes between two menu trees
This problem tests recursive tree traversal and hierarchical diffing strategies to identify structural and content changes between two versions of a menu tree.
Coding & AlgorithmsTechnical ScreenTreesRecursionHash Maps - DoorDashMediumSoftware EngineerCount changed nodes in N-ary trees
This question evaluates understanding of N-ary tree data structures, structural comparison of hierarchical versions, and the ability to reason about time and space complexity when detecting added, deleted, value-changed, or reparented nodes.
Coding & AlgorithmsTechnical Screen - DoorDashHardSoftware EngineerDebug a cache incident end-to-end
This question evaluates a candidate's ability to diagnose and debug production cache incidents, testing competencies in distributed caching, observability, incident response, root-cause analysis, and the operational impact on microservice latency.
Software Engineering FundamentalsTechnical Screen - DoorDashMediumSoftware EngineerDebug round-robin request router
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 Debug round-robin request router states assumptions, handles edge cases, explains trade-offs, and shows how to validate the result clearly.
System DesignTechnical Screen - DoorDashMediumSoftware EngineerDebug round-robin, DashMap, and simple cache
This question evaluates skills in concurrent programming and stateful selection logic (round-robin load balancing), data structure invariants and debugging (custom hash map hashing vs equality, collision resolution, resizing and iterator correctness), simple in-memory caching strategies with TTL or size-based eviction, and unit test design.
Coding & AlgorithmsTechnical Screen - DoorDashHardSoftware EngineerDeep-dive a project architecture
An open-ended DoorDash software-engineer system-design screen: pick a real project and deep-dive its architecture end to end. Candidates draw the diagram, state invariants, walk read/write paths, justify storage and trade-offs, capacity-plan, cover reliability/security/observability with SLOs, recount a real incident, and propose a quantified 10x-traffic plan. Includes a full worked example built around a real-time delivery dispatch and live order-tracking service.
System DesignTechnical Screen - DoorDashMediumSoftware EngineerDefend an Ownership Project with Measurable Impact
Tests an engineer's ability to demonstrate end-to-end ownership, justify architectural trade-offs under constraints, and prove business or operational impact using credible metrics.
Behavioral & LeadershipTechnical ScreenOwnershipSystem ArchitectureMetrics & Impact - DoorDashMediumSoftware EngineerDemonstrate leadership and team development
Demonstrate leadership and team development evaluates behavioral evidence, ownership, communication, trade-offs, and measurable outcomes in a realistic interview setting. A strong answer states assumptions, handles edge cases, explains trade-offs, and shows how to validate the result clearly.
Behavioral & LeadershipTechnical Screen - DoorDashMediumSoftware EngineerDescribe a Project End-to-End
This question evaluates a candidate's ability to demonstrate end-to-end project ownership, technical decision-making, cross-functional communication, and measurement of business impact, and is commonly asked to assess how an individual explains their role, trade-offs, launch outcomes, and lessons learned.
Behavioral & LeadershipTechnical Screen - DoorDashHardData ScientistDesign A/B Test to Evaluate Algorithm's Revenue Impact
DoorDash statistics and experimentation prompt on A/B testing a recommendation algorithm's revenue impact, covering hypotheses, randomization, sample size, heavy-tailed revenue, p=0.08 interpretation, and causal alternatives.
Statistics & MathTechnical Screen - DoorDashMediumSoftware EngineerDesign API that aggregates three downstream APIs
This question evaluates a candidate's ability to design an API aggregator, covering skills in service orchestration, fault tolerance, latency and SLO management, error handling, and observability for distributed HTTP/JSON services.
System DesignTechnical Screen - DoorDashMediumData ScientistDesign Biker metrics and A/B test plan
This question tests the ability to design an experimentation framework for a two-sided marketplace, focusing on metric definition, causal inference, and identifying potential gaming behaviors in delivery logistics.
Analytics & ExperimentationTechnical ScreenA/B TestingMarketplace AnalyticsMetric Design - DoorDashHardSoftware EngineerDesign Real-Time Driver Pay Aggregation
This 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.
System DesignTechnical Screen - DoorDashMediumSoftware EngineerDesign a Customer Review Page
This question tests the ability to design a scalable review system capable of handling high-write volume, media storage, and efficient retrieval with pagination.
System DesignTechnical ScreenAPIDatabaseScalability - DoorDashMediumSoftware EngineerDesign a Resilient Bootstrap API Aggregator
Design a resilient bootstrap aggregation service that fetches critical initial state for a mobile app on launch. Tests interface design, concurrent I/O, partial failure handling, and operational trade-offs.
Software Engineering FundamentalsTechnical ScreenAPI DesignConcurrencyResilience - DoorDashHardSoftware EngineerDesign a notification system
This 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.
System DesignTechnical Screen - DoorDashMediumSoftware EngineerDesign a resilient bootstrap API
This 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.
System DesignTechnical Screen - DoorDashHardSoftware EngineerDesign a resilient dasher payment system
A 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.
System DesignTechnical Screen - DoorDashHardSoftware EngineerDesign a scalable Instagram-like platform
Design 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.
System DesignTechnical Screen - DoorDashHardSoftware EngineerDesign a service aggregator with robust error handling
Design 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.
System DesignTechnical Screen - DoorDashMediumSoftware EngineerDesign a single-machine LRU cache
This question evaluates a candidate's ability to design an efficient in-memory LRU cache and apply concurrency control, covering eviction semantics, capacity management, key updates, and synchronization for thread safety.
Coding & AlgorithmsTechnical Screen - DoorDashMediumSoftware EngineerDesign an Alert Notification Service for Downstream Consumers
Design 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.
System DesignTechnical ScreenDistributed SystemsMessage QueuesEvent-Driven - DoorDashHardData ScientistDesign analysis to reduce cold-delivery complaints
This problem tests the ability to diagnose a service quality issue, define key performance indicators, and design an experiment to evaluate an operational intervention while controlling for confounding variables.
Analytics & ExperimentationTechnical ScreenCausal InferenceExperimental DesignProduct Metrics - DoorDashHardData ScientistDesign and analyze a switchback experiment
This question evaluates proficiency in experimental design, causal inference, randomization and contamination control, regression modeling with fixed effects and clustered standard errors, power calculation, and handling of compliance and robustness issues.
Analytics & ExperimentationTechnical Screen - DoorDashMediumSoftware EngineerDesign consistent hashing with a sorted map
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.
System DesignTechnical Screen - DoorDashMediumSoftware EngineerDesign hierarchical path store with create/set/get/remove
This question evaluates a candidate's competency in hierarchical data structures, path parsing, API semantics, error signaling, complexity analysis, and unit testing for implementing a UNIX-style key-value path store.
Coding & AlgorithmsTechnical Screen - DoorDashHardSoftware EngineerDesign limited-time donation platform
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.
System DesignTechnical Screen - DoorDashHardSoftware EngineerDesign notification and project architecture
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.
System DesignTechnical Screen - DoorDashMediumMachine Learning EngineerDesign personalized restaurant search and recommendations
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.
System DesignTechnical ScreenRecommendation SystemsRankingSearch - DoorDashMediumData ScientistDetermine Success Metrics for Biker Dasher Program Launch
This interview question evaluates metric design, causal reasoning, experiment setup, diagnostics, SQL/statistical checks, and recommendations in a realistic interview setting. A strong answer for Determine Success Metrics for Biker Dasher Program Launch states assumptions, handles edge cases, explains trade-offs, and shows how to validate the result clearly.
Analytics & ExperimentationTechnical Screen
DoorDash