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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 271–300 of 9403 results
- Akuna CapitalMediumSoftware EngineerImplement a ring buffer
This question evaluates implementation skills for fixed-capacity circular buffers and competency in array-based data structures, including O(1) push/pop/peek/isEmpty/isFull/size operations and logical-order iteration.
Coding & AlgorithmsTechnical Screen - Akuna CapitalMediumSoftware EngineerImplement a two-user communications handler
This question evaluates skills in stateful resource management, API and abstraction design, custom exception handling, and input validation for enforcing a single-active connection between two users.
System DesignOnline Assessment - Akuna CapitalHardSoftware EngineerMaximize Distinct Values with Cross-Array Swaps
This problem tests greedy strategy optimization and frequency counting to maximize the count of unique elements across two arrays after a limited number of swaps.
Coding & AlgorithmsTechnical ScreenGreedyArraysHashing - Akuna CapitalMediumData ScientistMaximize profitable pairs
This interview question evaluates algorithm design, data structures, correctness, complexity, edge cases, and implementation details in a realistic interview setting. A strong answer for Maximize profitable pairs states assumptions, handles edge cases, explains trade-offs, and shows how to validate the result clearly.
Coding & AlgorithmsTechnical Screen - Akuna CapitalHardSoftware EngineerMinimum Movement Cost to Segregate Binary Digits
This problem tests greedy algorithm design and sequence optimization by calculating the cumulative distance required to shift all '1's to the end of a binary string.
Coding & AlgorithmsTechnical ScreenGreedyStringsArrays - Akuna CapitalMediumSoftware EngineerSolve swaps, graph paths, and movie DP
This interview question evaluates algorithm design, data structures, correctness, complexity, edge cases, and implementation details in a realistic interview setting. A strong answer for Solve swaps, graph paths, and movie DP states assumptions, handles edge cases, explains trade-offs, and shows how to validate the result clearly.
Coding & AlgorithmsOnline Assessment - Akuna CapitalMediumSoftware EngineerSolve three C++ algorithmic tasks
This interview question evaluates algorithm design, data structures, correctness, complexity, edge cases, and implementation details in a realistic interview setting. A strong answer for Solve three C++ algorithmic tasks states assumptions, handles edge cases, explains trade-offs, and shows how to validate the result clearly.
Coding & AlgorithmsOnline Assessment - Akuna CapitalMediumSoftware EngineerTrace code and find frequent character
Trace code and find frequent character 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.
Coding & AlgorithmsOnline Assessment - Akuna CapitalMediumData EngineerWrite February Resource Usage Query
This question tests the ability to join multiple tables, handle date filtering with range conditions, and perform grouped aggregations to calculate average metrics across different resource categories.
Software Engineering FundamentalsOnline AssessmentSQLAggregationJoins - AlibabaMediumSoftware EngineerExplain What Your Team Owns and Why It Needs Its Headcount
A resume deep-dive question asking a software engineer to explain what their team owns, why it needs its current number of engineers, and one concrete example that shows the work is harder than it looks. It tests system-level understanding, judgment about complexity and composure when the interviewer says the business sounds simple.
Behavioral & LeadershipTechnical Screen - AlibabaMediumSoftware EngineerFixed-Capacity Cache That Evicts the Least Frequently Used Key, Ties by Recency
Build a fixed-capacity key-value cache that evicts the key with the fewest uses, breaking ties by least recent use, and replay a sequence of get and put operations to return each read result. It tests careful per-key frequency and recency tracking with constant average time per operation.
Coding & AlgorithmsTechnical Screen - AlibabaMediumSoftware EngineerIdempotent Kafka Consumer: Duplicate Writes, Offset Commits and a Second Database
A backend design discussion on making a concurrent Kafka consumer idempotent: how to stop duplicate effects when the same message is processed twice, whether a duplicate write should throw or return the existing data, how offsets keep advancing, and how to keep a second database consistent when publishing fails.
System DesignTechnical Screen - AltruistHardSoftware EngineerDesign scalable rate limiter with token bucket
This question evaluates understanding of rate-limiting algorithms and scalability concepts, specifically comparing sliding-window and token-bucket approaches with attention to lazy refill, per-client state modeling, memory efficiency, concurrency, and extendability to distributed systems.
System DesignTechnical Screen - AmazonMediumSoftware EngineerA Problem That Needed Deep Analysis: Knowing You Focused on the Right Things
A behavioral question about a problem that required in-depth thought and analysis, how you knew you were focusing on the right things, and what the outcome was. Follow-ups probe precise details of the example, such as an LLM agent's token size, the effect of adding fields, and what completeness meant.
Behavioral & LeadershipOnsite - AmazonMediumSoftware EngineerAccept Notification Bursts With Low Latency
Design a high-throughput, low-latency notification ingestion and delivery service capable of absorbing sudden 10x traffic spikes while maintaining strict delivery SLOs and downstream rate limits.
System DesignTechnical ScreenDistributed SystemsMicroservicesMessage Queues - AmazonMediumSoftware EngineerAdd One Source to Minimize Grid Inconvenience
Minimize the worst inconvenience in a binary grid by adding one colored source. Movement is allowed in eight directions, and the solution must handle grids that begin with no source at all.
Coding & AlgorithmsOnline Assessment - AmazonHardProduct ManagerAlexa Domain-Knowledge Data Pipelines
Practice an Alexa knowledge-pipeline system design covering global holidays, animal facts, source reliability, ingestion, calendar normalization, knowledge graphs, answer serving, entity linking, confidence thresholds, misrouted queries, and debugging.
Product / Decision MakingOnsite - AmazonMediumProduct ManagerAmazon Behavioral Deep-Dive
Prepare for the Amazon PM behavioral deep-dive with a reusable STAR story bank mapped to Leadership Principles. The guide organizes prompts across fit, data, innovation, conflict, trust, coaching, failure, crisis, integrity, and time management, with metrics and probe-ready follow-up details.
Behavioral & LeadershipOther - AmazonMediumProduct ManagerAmazon Fit, Motivation & Leadership Principles
Practice Amazon Product Manager fit and behavioral questions covering why Amazon, why this PM role, changing direction mid-project, fast decisions with limited information, and five-year career goals. The solution emphasizes customer obsession, metrics, guardrails, ownership, and leadership principles.
Behavioral & LeadershipOnsite - AmazonMediumProduct ManagerAmazon Leadership Principles Behavioral Scenarios
A consolidated bank of 24 Amazon product manager onsite behavioral questions, covering dive deep and root-cause analysis, scaling, influence and disagreement, customer obsession, ownership, mistakes and missed commitments, decisions under ambiguity, Think Big, and one cloud-connectivity triage hypothetical. Each prompt comes with a worked STAR outline, quantified results, and the Leadership Principles the interviewer is scoring. Includes a story-bank map that collapses all 24 prompts into 10 to 12 reusable stories.
Behavioral & LeadershipOnsite - AmazonMediumProduct ManagerAmazon Leadership Principles – Behavioral Deep Dive
Full Amazon Product Manager onsite behavioral loop: 25 Leadership Principles STAR prompts collected from real interview reports, covering customer obsession, dive deep, data-heavy projects, bias for action, ownership, simplification, conflict, missed commitments, failure, and long-term trade-offs. Each prompt comes with what interviewers score, a metrics-backed model answer, and the pitfalls that sink candidates. Includes a story-bank strategy, a reusable STAR template, and the follow-ups to expect.
Behavioral & LeadershipOnsite - AmazonHardProduct ManagerAmazon New-Service Launch Cases
Practice Amazon new-service launch cases for table booking, flower delivery, and advertising platforms. The solution covers target users, JTBD, MVP scope, architecture, metrics, GTM, risks, Working Backwards framing, and long-term flywheels.
Product / Decision MakingOnsite - AmazonMediumBusiness Intelligence EngineerAnalyze Seller Compliance and Customer Purchase Patterns
This question evaluates a candidate's ability to manipulate and analyze temporal and categorical datasets, covering competencies such as event sequencing, set-based filtering, and cross-table aggregation in SQL/Python.
Data Manipulation (SQL/Python)Onsite - AmazonMediumData ScientistAnalyze Top 10 Items' Revenue Contribution by Category
This question evaluates proficiency in data manipulation and analytical querying—aggregation, window functions, ranking and revenue attribution—alongside conceptual knowledge of normalization versus denormalization and ETL pipeline design.
Data Manipulation (SQL/Python)Onsite - AmazonHardData ScientistAnalyze an A/B test over last 7 days
This question evaluates competency in A/B test analysis and experiment design, covering conversion-rate computation, statistical inference (two-proportion testing and confidence intervals), sample-ratio checks, heterogeneity assessment (fixed versus random effects), and power/MDE reasoning.
Analytics & ExperimentationOnsite - AmazonEasyData EngineerAnswer Amazon Behavioral Questions
Three classic Amazon final-round behavioral questions — a significant challenge you overcame, motivating a struggling team, and why Amazon — answered with the STAR framework and Amazon Leadership Principles. Each answer emphasizes ownership, problem solving, collaboration, and quantified impact.
Behavioral & LeadershipTechnical Screen - AmazonEasyData ScientistAnswer Amazon Leadership Principle Scenarios
This question evaluates behavioral competencies relevant to a Data Scientist intern, including leadership, communication, decision-making under uncertainty, risk assessment, time management, teamwork, learning agility, and motivation for the role.
Behavioral & LeadershipOnsite - AmazonMediumSoftware EngineerAnswer Amazon Leadership Principles questions
This interview question evaluates behavioral evidence, ownership, communication, trade-offs, and measurable outcomes in a realistic interview setting. A strong answer for Answer Amazon Leadership Principles questions states assumptions, handles edge cases, explains trade-offs, and shows how to validate the result clearly.
Behavioral & LeadershipOnsite - AmazonMediumTechnical Program ManagerAnswer Amazon leadership behaviorals
Prepare senior Amazon L6 program-management behavioral answers for unconventional problem solving, stakeholder disagreement, ownership outside scope, team speed, and tough feedback. The solution emphasizes STAR structure, mechanisms, leadership principles, and measurable impact.
Behavioral & LeadershipOnsite - AmazonEasyData ScientistAnswer Amazon-style behavioral questions
This question evaluates interpersonal leadership, communication, and impact-oriented decision-making for a Data Scientist, testing competencies such as handling workplace challenges, motivating teams, and tying experiences to organizational leadership principles.
Behavioral & LeadershipTechnical Screen
Akuna Capital
Alibaba
Amazon