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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
- Topics
- 8
- Languages
Showing 1501–1530 of 4616 results
- DuolingoEasySoftware EngineerImplement String Encryption and Decryption
This problem tests your ability to manage character mapping and reverse lookups using dictionaries to perform basic string transformation and reconstruction.
Coding & AlgorithmsTechnical ScreenStringsDictionariesHash Maps - EYMediumData ScientistArchitect cloud data ingestion patterns
This question evaluates a candidate's ability to design end-to-end cloud data ingestion and serving architectures, including streaming and batch patterns, CDC/event sourcing/micro-batch trade-offs, partitioning and compaction strategies, idempotency, schema evolution, PII tokenization, cost controls, and incident simulation for chaos testing.
Data Manipulation (SQL/Python)Technical Screen - EYMediumData ScientistDesign logical model and consumption
This question evaluates understanding of logical data modeling, ERD-level design with keys and cardinalities, slowly changing dimensions, normalization versus denormalization trade-offs, and strategies for exposing curated datasets and read paths for analytics and regulatory consumers, indicating competency in data modeling and data delivery.
Data Manipulation (SQL/Python)Technical Screen - EYMediumData ScientistMap sources to functional dataset with SQL
This question evaluates competency in SQL-based data manipulation and data engineering concepts, including handling late-arriving data and deduplication to the latest ingested record, joining and filtering for enrichment and KYC status, and computing exposure metrics such as gross/net notional, limit utilization, and breach flags.
Data Manipulation (SQL/Python)Technical Screen - EYMediumData ScientistWalk through end‑to‑end delivery
This question evaluates leadership and program-management competencies specific to data science, including end-to-end project ownership, cross-functional coordination, risk identification and mitigation, and production of phase artifacts.
Behavioral & LeadershipTechnical Screen - EarninMediumData AnalystDefend the Decisions Behind a High-Impact Data Project
Prepare a senior project deep dive connecting a real business decision to your analytical choices, alternatives, validation, influence, and measured outcome. The exercise helps you show ownership, technical judgment, honest attribution, and reflection under probing follow-ups.
Behavioral & LeadershipTechnical Screen - EarninMediumData AnalystExplain an Innovative Analytical Method You Introduced
Practice presenting an innovative analytics method as a decision-focused story: identify the weak baseline, explain your contribution and tradeoffs, validate the improvement fairly, earn stakeholder adoption, and discuss measurable impact and lessons.
Behavioral & LeadershipTechnical Screen - EarninMediumData AnalystResolve a Cross-Functional Data Disagreement
Prepare for senior behavioral questions about cross-functional conflict by separating evidence, goals, constraints, and decision rights. Practice building shared criteria, proposing safe tests, communicating uncertainty, and owning execution after alignment.
Behavioral & LeadershipTechnical Screen - EaseHardSoftware EngineerBuild a Hash-Table Key-Value Store Without Built-in Dictionaries or Sets
Implement a key-value store class with put, get and remove without using built-in dictionaries or sets, resolving collisions inside the store rather than raising them to callers. It tests hash table mechanics, collision strategies, deletion, resizing and precise average versus worst-case complexity claims.
Software Engineering FundamentalsTechnical Screen - EightfoldaiMediumSoftware EngineerMake a Parentheses String Valid
This question evaluates proficiency in string manipulation and delimiter matching, specifically balancing parentheses while preserving character order and handling edge cases.
Coding & AlgorithmsTechnical Screen - ElasticMediumSoftware EngineerImplement log aggregation in React
This question evaluates a candidate's front-end development and real-time data-aggregation skills, specifically React component state management, handling streaming updates, choosing appropriate in-memory data structures (e.g., Map), and timestamp parsing/comparison for per-category frequency and last-update tracking.
Coding & AlgorithmsTechnical Screen - ElasticMediumSoftware EngineerReview a JavaScript flatten PR
This question evaluates a candidate's understanding of JavaScript recursion, array manipulation, API contract reasoning, and correctness when implementing a flatten utility.
Software Engineering FundamentalsTechnical Screen - EliseAIMediumSoftware EngineerAnalyze the Fairness of an Incremental Shuffle
This question tests the ability to analyze algorithm correctness through probability theory and identify common pitfalls in pseudo-random number generation that lead to selection bias.
Software Engineering FundamentalsTechnical ScreenAlgorithmsProbabilityShuffle - EliseAIEasySoftware EngineerDescribe Something a Previous Engineering Team Did Not Do Well
A behavioral question asking what a previous engineering team did not do well. Tests whether a candidate can name a specific, fixable weakness, explain its cost and systemic cause, describe their own part in improving it and stay constructive without blaming former colleagues.
Behavioral & LeadershipTechnical Screen - EliseAIMediumSoftware EngineerExplain a Technical Decision and Transferable Team Practice
This question assesses the candidate's ability to articulate technical trade-offs, reflect on past architectural decisions, and demonstrate maturity in implementing new engineering processes within an existing team culture.
Behavioral & LeadershipTechnical ScreenLeadershipCommunicationEngineering Process - EliseAIEasySoftware EngineerIntroduce Yourself and Explain What You Want in Your Next Engineering Role
The opening of a software engineer phone screen: give a concise introduction of yourself and explain what you are looking for in your next role. Tests narrative structure, the choice of specific highlights that set up a technical deep dive, and motivation that is backed by evidence and fits the role.
Behavioral & LeadershipTechnical Screen - EliseAIMediumData ScientistLease Renewal Prediction and Non-Renewal Reason Categorization Take-Home
A machine learning take-home on predicting lease renewals from tenant conversations and SQLite tables of residents, maintenance work orders and renewal offers. It covers preprocessing, a metric compared with a random baseline, a test-set prediction file, categorizing non-renewal reasons with gte-base embeddings, and presenting the results.
Machine LearningTechnical Screen - EliseAIEasySoftware EngineerRead and Critique a Short Python Function That Randomly Swaps List Elements
A code-reading exercise: assess a short Python function that walks a list and swaps each element with a randomly chosen position at or before it. Tests tracing unfamiliar code, reasoning about whether every ordering is equally likely, input-type edge cases such as strings, and practical code-review judgment.
Software Engineering FundamentalsTechnical Screen - EliseAIEasySoftware EngineerWalk Through a System You Built: Key Technical Decisions and the Hardest Part
Describe a technical system you implemented at a previous company, the technical decisions you made along the way and the hardest part of the work. Tests clear ownership, trade-off reasoning between real alternatives, technical depth under probing and honest reflection on what was difficult.
Behavioral & LeadershipTechnical Screen - EngelhartMediumSoftware EngineerDesign a Daily Weather-Forecast Pipeline That Runs Power Models for Energy Traders
Design a pipeline that ingests a weather forecast CSV published daily at a variable time, validates and stores it, runs black-box demand, wind, solar, hydro and price models across every scenario, and serves aggregated forecasts to traders. It tests scheduling, DAG design, failure handling, dashboard delivery and scaling to thousands of scenarios.
System DesignTechnical Screen - EngelhartMediumSoftware EngineerExposing a Python Function as a REST Endpoint with FastAPI and Unit Testing It
An interview question on exposing a Python function as a REST API endpoint and testing it. It asks whether FastAPI counts as an endpoint, how an endpoint maps an HTTP request onto a function, and how you unit test such code, with a concrete example that covers edge cases and replaced dependencies.
Software Engineering FundamentalsTechnical Screen - EngelhartMediumSoftware EngineerPython Abstract Classes and Instance, Class and Static Methods
A Python object-oriented programming interview question on abstract classes and method kinds. It asks what an abstract class is and whether it can be instantiated, how instance, class and static methods differ, what self and cls refer to, and why a static method would live inside a class at all.
Software Engineering FundamentalsTechnical Screen - EngelhartMediumSoftware EngineerPython Dictionary Internals: Hashing, Collisions, O(1) Lookup and Hashable Keys
A Python fundamentals interview question on how dictionaries store and look up values: what gets hashed, whether different keys can share a hash, how collisions are resolved and why average lookup is constant time. It also tests whether a list can serve as a key and which objects are allowed as keys.
Software Engineering FundamentalsTechnical Screen - EngelhartMediumSoftware EngineerPython Generators, yield, Lazy Evaluation and How Decorators Work
A Python interview question on generators and decorators. It asks what a generator is, what yield does, why generators use less memory and what lazy evaluation means, then what a decorator actually does under the hood, testing precise language mechanics rather than memorized definitions.
Software Engineering FundamentalsTechnical Screen - EngelhartMediumSoftware EngineerPython Virtual Environments, Conda and Poetry, and Everyday Linux Commands
A developer tooling interview question on Python virtual environments, why projects need them and how Conda and Poetry fit in, followed by practical Linux experience: which system you work on and which Unix commands you rely on to run and debug jobs on a server.
Software Engineering FundamentalsTechnical Screen - EngelhartMediumSoftware EngineerRelational Database Indexes: Read/Write Trade-offs and Tuning a Slow SQL Query
A database fundamentals interview question on relational indexes: what an index is, why it speeds up queries, why not every column should be indexed and how indexes affect write performance. It then asks how you would troubleshoot and tune a complex SQL query that runs extremely slowly.
Software Engineering FundamentalsTechnical Screen - EngelhartMediumSoftware EngineerThreads vs Processes, the Python GIL, Multiprocessing and Async I/O
A Python concurrency interview question covering how threads and processes differ, including their memory spaces, when to reach for multiprocessing, what the Global Interpreter Lock is and how it limits CPU-bound threads, and why async I/O is a good fit for network and other I/O-bound workloads.
Software Engineering FundamentalsTechnical Screen - EnigmaMediumSoftware EngineerSearch Book Titles
This question evaluates proficiency in string processing, tokenization, case-insensitive matching, anagram detection, and algorithmic design for efficient search and deduplication.
Coding & AlgorithmsTechnical Screen - EquinixMediumSoftware EngineerReview AI Platform And Software Fundamentals
This problem tests foundational knowledge in software architecture, AI system design, and data structures by requiring the candidate to explain the trade-offs in building a RAG-based document retrieval system.
Software Engineering FundamentalsTechnical ScreenRAGSystem DesignSOLID - EricssonMediumSoftware EngineerSolve Triangle Rows and Top Frequencies
This question set evaluates understanding of combinatorial number patterns and frequency-based selection, specifically the ability to generate an additive number triangle and to identify the k most frequent elements, assessing skills in array/list manipulation, counting, and selection algorithms.
Coding & AlgorithmsTechnical Screen
EY
EliseAI