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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
- Companies
- 11
- Topics
- 8
- Languages
Showing 1081–1110 of 3640 results
- DiscordMediumSoftware EngineerImplement an asyncio-based chat server
This question tests practical knowledge of Python's asyncio library and concurrent programming by requiring the implementation of a TCP chat server. It evaluates a software engineer's ability to manage multiple simultaneous connections, handle resource cleanup, and apply event-driven concurrency patterns — core competencies commonly assessed in backend and systems-focused interviews.
Coding & AlgorithmsOnsite - DisneyEasyData EngineerBehavioral Panel: Conflict, Critical Feedback, Competing Priorities and Culture Fit
Behavioral and culture-fit questions for a senior data engineer: a conflict, critical feedback, competing priorities, the motivation for moving into data engineering, and personal questions about turning points, best and worst managers, and disliked subjects. It tests self-awareness, ownership and clear storytelling.
Behavioral & LeadershipOnsite - DisneyMediumSoftware EngineerBuild a sortable, searchable movie list UI
This question tests the ability to design a performant, reactive frontend component that handles data manipulation, asynchronous API integration, and efficient DOM rendering.
Software Engineering FundamentalsOnsiteFrontendReactPerformance - DisneyEasyData EngineerData Pipeline Design for Cloud and Hybrid On-Prem Environments on AWS and Azure
A senior data engineering design question: build a data pipeline from operational sources to analytics on one cloud, then rework it for a hybrid on-premises and cloud environment and for both AWS and Azure. It tests tool selection and trade-offs, ingestion and storage design, data quality, security and portability.
System DesignOnsite - DisneyMediumSoftware EngineerDemonstrate culture fit and collaboration
This question evaluates interpersonal and leadership competencies for a Software Engineer, including culture fit, adaptability, communication, influencing without authority, conflict resolution, handling ambiguous requirements, and receptiveness to critical feedback within the Behavioral & Leadership domain.
Behavioral & LeadershipOnsite - DisneyMediumSoftware EngineerDesign a Flash Sale with a Virtual Queue and Exact Inventory
Design a high-scale ticketing and merchandise flash-sale platform featuring a virtual waiting room, controlled admission rate, strictly zero-oversell inventory reservation, and idempotent checkout.
System DesignOnsiteDistributed SystemsConcurrencyCaching - DisneyMediumSoftware EngineerDesign a Twitter-like microblogging platform
This problem tests your ability to design a distributed system capable of handling high-throughput write operations, efficient read-heavy feed generation, and the trade-offs between system consistency and availability.
System DesignOnsiteScalabilityCachingDistributed Systems - DisneyEasySoftware EngineerDesign a frontend shopping cart and feature flags
This question evaluates frontend system-design skills including client-side state management, synchronization and conflict-resolution strategies, caching and offline resilience, performance for large carts, observability, and feature-flag/remote-config design for targeted rollouts and experiments.
System DesignOnsite - DisneyHardSoftware EngineerDesign a global multi-game leaderboard
This question evaluates a candidate's ability to design a scalable, real-time distributed leaderboard service, testing skills in API design, data modeling, ranking algorithms, ingestion and read-path architecture, caching, sharding, consistency-versus-latency trade-offs, idempotency, anti-cheat measures, and disaster recovery.
System DesignOnsite - DisneyEasySoftware EngineerHow do you manage collaboration and stakeholders?
This question evaluates leadership competencies such as stakeholder management, cross-functional collaboration, conflict resolution, prioritization of trade-offs, and influence within a software engineering context.
Behavioral & LeadershipOnsite - DisneyEasySoftware EngineerHow would you run a mentoring-focused code review?
This question evaluates mentoring-focused code review competencies, including code quality and maintainability analysis, frontend architecture (React/TypeScript), testing strategy, accessibility and security awareness, plus written and interpersonal feedback skills.
Software Engineering FundamentalsOnsite - DisneyMediumSoftware EngineerImplement an LRU cache
This problem tests your ability to design a cache that supports O(1) access, insertion, and eviction by combining two core data structures.
Coding & AlgorithmsOnsiteHash TableDoubly Linked ListDesign - DisneyEasyData EngineerPrompting an LLM to Migrate a Java Codebase to Python and Clean a Large Database
Explain how you would prompt a large language model to migrate a Java codebase to Python and to help clean a database with tens of thousands of rows. It tests prompt design, verification of generated code and data fixes, data quality measurement, security of AI-assisted work and the handling of sensitive data.
Software Engineering FundamentalsOnsite - DisneyMediumSoftware EngineerSolve grid shortest path with BFS
This question evaluates understanding of grid traversal and shortest-path graph search, including modeling a 2D grid with obstacles and reasoning about boundary and edge cases, within the Coding & Algorithms domain.
Coding & AlgorithmsOnsite - DistylMediumMachine Learning EngineerDesign Streaming Speech and Multi-Model Chat Systems
A two-part system-design interview covering incremental multi-speaker transcription and a streaming multi-model chat service. Candidates must reason about ordering, revisions, backpressure, model fallback, durable conversation state, safety, and recovery.
ML System DesignOnsite - DocuSignEasySoftware EngineerCompress Consecutive Integer Ranges
Tests array manipulation, sorting, deduplication, and range-grouping logic to produce a compact string representation of consecutive numbers.
Coding & AlgorithmsOnsitearrayssortingstring - DocuSignEasySoftware EngineerDesign a JSON Schema Validator
Design and implement a modular JSON schema validator that verifies data against structural schemas, supporting primitive types, nested objects, arrays, regex patterns, numeric ranges, and strict field controls.
Software Engineering FundamentalsOnsiterecursionoopdesign - DocuSignMediumSoftware EngineerImplement a key-value CRUD store
This question evaluates understanding of core data structures, API design, complexity analysis, and edge-case handling for an in-memory key–value CRUD store, and falls under the Coding & Algorithms domain while testing both practical implementation skills and conceptual reasoning about time/space trade-offs.
Coding & AlgorithmsOnsite - DoorDashMediumSoftware EngineerAnswer feedback, conflict, and failure questions
This set of behavioral prompts evaluates interpersonal communication, the ability to give and receive constructive feedback, conflict resolution, accountability for mistakes, and motivation for joining the employer.
Behavioral & LeadershipOnsite - DoorDashMediumData ScientistBoost App Installs: Analyze and Experiment with Conversion Funnel
DoorDash analytics prompt on improving mobile web to app-install conversion, covering funnel measurement, attribution, cohorts, install and activation experiments, incentives, guardrails, and long-term retention impact.
Analytics & ExperimentationOnsite - DoorDashMediumSoftware EngineerBootstrap Service: Aggregate Downstream Services and Return the Right HTTP Status
Implement a bootstrap service that calls several independent downstream services concurrently, aggregates their data into one response for a client app, and returns an HTTP status code that reflects partial or total failure. It tests concurrent calls, timeouts, per-section error reporting, and mapping downstream failures to client-facing status codes.
Software Engineering FundamentalsOnsite - DoorDashHardData ScientistBuild ETA prediction and simulate impact
This question evaluates machine learning competencies for ETA prediction, including feature engineering, leakage detection, time-based validation, point and quantile modeling, evaluation and calibration metrics, cost-sensitive decisioning, explainability and fairness auditing, and production deployment considerations.
Machine LearningOnsite - DoorDashMediumSoftware EngineerBuild Resilient Aggregation and Debug Routing
This question evaluates skills in building resilient API aggregation, fault-tolerant retry handling and test coverage for transient failures, as well as debugging and improving load-balancer routing policies including adding round-robin distribution and reasoning about consistent hashing.
Software Engineering FundamentalsOnsite - DoorDashMediumSoftware EngineerBuild Two Interacting Services That Carry Out a Realistic Refund Flow
A senior coding exercise, with an AI assistant allowed, to build two cooperating services that carry out a refund end to end. It tests service boundaries, a refund state machine, idempotent retries, handling of declines and timeouts, and a runnable simulation of realistic refund scenarios.
Software Engineering FundamentalsOnsite - DoorDashMediumSoftware EngineerBuild a Resilient Bootstrap API with Partial Upstream Results
Combine Consumer, Payment, and Address APIs with correct identifier dependencies, partial success, bounded timeouts, and complete response fields.
Software Engineering FundamentalsOnsite - DoorDashMediumSoftware EngineerBuild a Running Late-Order Refund Workflow as Separate Python Services
Build a continuously running Python system of separate services that executes a small workflow graph in which late orders trigger refunds, then discuss new features, API evolution, adding payments, and testing. It tests scoping under time pressure, service boundaries, idempotent refunds, and effective AI-assisted development.
Software Engineering FundamentalsOnsite - DoorDashHardData ScientistBuild a late-delivery risk model
This question evaluates competencies in production-ready predictive modeling, including target definition, feature engineering, temporal train/validation splitting to avoid leakage, model evaluation and calibration, monitoring and ramp strategies, and translating probabilistic outputs into business-impacting decisions for a Data Scientist.
Machine LearningOnsite - DoorDashMediumSoftware EngineerBuild an Order-Exception Microservice with Explicit Refund Policies
Design and demonstrate a local service for missing or delayed orders, with explicit refund rules, duplicate handling, and auditable decisions.
Software Engineering FundamentalsOnsite - DoorDashMediumSoftware EngineerBuild and Debug a Dasher-to-Order Assignment Service, Then Prepare It for Production
A DoorDash onsite exercise to finish and debug starter code for a service that assigns delivery drivers to orders. It tests constant-time bookkeeping, defending a list versus hash map storage choice, invariant-based testing, and how to make the service safe and scalable in production.
Software Engineering FundamentalsOnsite - DoorDashMediumSoftware EngineerCalculate Driver Payments
Implement a payout calculation system for delivery drivers by deduplicating order logs, merging overlapping active-time intervals, and computing base pay, delivery bonuses, and tips.
Coding & AlgorithmsOnsiteintervalssortinghash-table
Discord
Disney
DocuSign
DoorDash