DoorDash interview questions

Showing 31–60 of 241 results

• Compute courier pay with peak-hour rulesMedium

  This question evaluates a candidate's data manipulation skills and competency in implementing business rules, including robust error handling, aggregation for per-day totals, minimum-pay enforcement, and time-window (peak-hour) pay adjustments.

  DoorDashSoftware EngineerData Manipulation (SQL/Python)Technical Screen
• Compute dasher pay from deliveriesMedium

  This question evaluates competency in data manipulation, schema design and validation, time-based aggregation, pay-computation logic, and handling of edge cases using SQL or Python.

  DoorDashSoftware EngineerData Manipulation (SQL/Python)Onsite
• Compute dasher pay with peak-hour queryMedium

  This question tests the ability to handle overlapping time intervals and perform weighted calculations based on time-based pay multipliers.

  DoorDashSoftware EngineerCoding & AlgorithmsOnsite
• Compute dasher payout from API dataMedium

  This question evaluates a candidate's proficiency in data manipulation and transaction aggregation using SQL or Python, encompassing time-zone-aware timestamp handling, pagination, late or missing events, cancellations and negative adjustments, rounding rules, and itemized breakdowns.

  DoorDashSoftware EngineerData Manipulation (SQL/Python)Onsite
• Compute delivery times on a gridMedium

  This question evaluates understanding of graph traversal and shortest-path algorithms, grid-based pathfinding, and data structure selection for representing sparse or large grids within the Coding & Algorithms domain.

  DoorDashSoftware EngineerCoding & AlgorithmsTechnical Screen
• Compute earliest arrival in time-gridMedium

  This question evaluates algorithmic problem-solving and pathfinding skills on grid-based graphs, focusing on modeling time-dependent traversal constraints and reasoning about efficient search and supporting data structures.

  DoorDashSoftware EngineerCoding & AlgorithmsTechnical Screen
• Compute nearest dashmart and busiest assignmentsMedium

  Compute nearest dashmart and busiest assignments evaluates algorithm design, data structures, correctness, complexity, edge cases, and implementation details 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 EngineerCoding & AlgorithmsTechnical Screen
• Compute nearest dashmart distances for queriesMedium

  This question evaluates a candidate's understanding of graph traversal and shortest-path computation on grids, spatial reasoning about obstacles and sources, and the ability to analyze algorithmic scalability and complexity when answering many queries.

  DoorDashSoftware EngineerCoding & AlgorithmsTechnical Screen
• Compute nearest-exit distances in a gridMedium

  Compute nearest-exit distances in a grid evaluates algorithm design, data structures, correctness, complexity, edge cases, and implementation details 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 EngineerCoding & AlgorithmsOnsite
• Compute rolling cold-delivery rates with windowsMedium

  This question evaluates proficiency with SQL window functions, time-based joins, event deduplication and business-rule implementation for computing rolling metrics over temporal windows.

  DoorDashData ScientistData Manipulation (SQL/Python)Onsite
• Compute sample sizes and error controlMedium

  This question evaluates proficiency in experimental design and applied inferential statistics—specifically sample size calculation for means and proportions, non-inferiority testing, multiple-comparison error control, cluster-randomized design effects, and sequential monitoring boundaries—within the Statistics & Math domain for a Data Scientist role. It is commonly asked to measure the ability to apply statistical formulas and error-control principles under practical constraints, balancing power and type I error while accounting for clustering and interim looks; the assessment emphasizes practical application grounded in conceptual understanding of inferential methods.

  DoorDashData ScientistStatistics & MathTechnical Screen
• Count changed nodes between two menu treesHard

  This problem tests recursive tree traversal and hierarchical diffing strategies to identify structural and content changes between two versions of a menu tree.

  DoorDashSoftware EngineerCoding & AlgorithmsTechnical Screen
• Count changed nodes in N-ary treesMedium

  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.

  DoorDashSoftware EngineerCoding & AlgorithmsTechnical Screen
• Debug Round-Robin and Consistent-Hash RoutingMedium

  This problem tests the ability to identify flaws in load balancing implementations by evaluating consistency, distribution, and edge-case handling in Round-Robin and Consistent Hashing logic.

  DoorDashSoftware EngineerSoftware Engineering FundamentalsOnsite
• Debug a Random Dasher RegistryMedium

  Debug a random dasher registry backed by a dense array and an ID-to-index map. Repair empty and swap-delete edge cases, preserve representation invariants, narrow error handling, and extend the design for concurrency and slow dependencies.

  DoorDashSoftware EngineerSoftware Engineering FundamentalsOnsite
• Debug a Round-Robin Load Balancer, Then Implement Consistent HashingMedium

  Debug a round-robin load balancer that must keep strict rotation while servers are added and removed, then implement a consistent-hash ring that gives each key a stable server. It tests off-by-one and index-mutation bugs, thread safety, stable hashing, virtual nodes, lookup cost, and how many keys move on membership changes.

  DoorDashSoftware EngineerSoftware Engineering FundamentalsOnsite
• Debug a cache incident end-to-endHard

  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.

  DoorDashSoftware EngineerSoftware Engineering FundamentalsTechnical Screen
• Debug a driver assignment bugMedium

  This question evaluates debugging, root-cause analysis, unit/integration test design, observability, and system-resilience competencies within the Coding & Algorithms domain, emphasizing practical skills in reproducing failures, isolating defects, and implementing targeted fixes.

  DoorDashSoftware EngineerCoding & AlgorithmsOnsite
• Debug and refactor a legacy moduleMedium

  This question evaluates debugging, refactoring, naming and exception handling, input validation, code structure, and concurrency-safety design skills within a legacy codebase, requiring both hands-on code changes and higher-level reasoning about immutability, confinement, synchronization, and concurrent data structures.

  DoorDashSoftware EngineerCoding & AlgorithmsOnsite
• Debug round-robin request routerMedium

  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.

  DoorDashSoftware EngineerSystem DesignTechnical Screen
• Debug round-robin, DashMap, and simple cacheMedium

  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.

  DoorDashSoftware EngineerCoding & AlgorithmsTechnical Screen
• Debug the Last-Element Random Allocation CaseHard

  Implement and test an O(1) randomized pool that avoids and deterministically tests against the classic self-swap regression when removing the tail element.

  DoorDashSoftware EngineerSoftware Engineering FundamentalsOnsite
• Debug using logs and allocate tasksMedium

  This question evaluates a candidate's skill in log-driven debugging, production incident investigation, and cross-functional task allocation, covering competencies such as structured and contextual logging, correlation identifiers, noise reduction, minimal reproducibility, feature-flagged isolation, triage coordination, hypothesis tracking, root-cause confirmation, regression prevention, and blameless postmortems. It is commonly asked to assess operational troubleshooting and teamwork under production uncertainty within the Coding & Algorithms category, testing practical application of debugging techniques alongside conceptual understanding of incident management and process-level coordination.

  DoorDashSoftware EngineerCoding & AlgorithmsOnsite
• Decide and test a 20% discount strategyHard

  This question tests the ability to design a controlled experiment to evaluate a promotional discount strategy, focusing on causality, profit optimization, and long-term customer value impact.

  DoorDashData ScientistAnalytics & ExperimentationOnsite
• Decompose and optimize delivery operational costsHard

  This question evaluates a data scientist's ability to decompose per-order operational costs, identify high-impact levers to reduce unit economics, and design rigorous experiments and monitoring for a two-sided delivery marketplace, testing competencies in cost modeling, causal inference, experimentation design, and product analytics.

  DoorDashData ScientistAnalytics & ExperimentationOnsite
• Deep-dive a project architectureHard

  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.

  DoorDashSoftware EngineerSystem DesignTechnical Screen
• Defend an Ownership Project with Measurable ImpactMedium

  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.

  DoorDashSoftware EngineerBehavioral & LeadershipTechnical Screen
• Define and compute retention and churn preciselyHard

  This question evaluates a Data Scientist's competency in statistical measurement of user retention and churn, covering cohort definition, activity rules, risk-set-aware retention and churn formulas, censoring and delayed conversion handling, and survival-analysis concepts like time-to-churn, hazard, and cumulative incidence.

  DoorDashData ScientistStatistics & MathOnsite
• Define metrics for new market expansion successHard

  This question tests the ability to design a comprehensive evaluation framework for entering a new geographic market by balancing growth, unit economics, and marketplace balance.

  DoorDashData ScientistAnalytics & ExperimentationOnsite
• Demonstrate leadership and team developmentMedium

  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.

  DoorDashSoftware EngineerBehavioral & LeadershipTechnical Screen