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Data Engineer 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 31–60 of 129 results
- Capital OneMediumData EngineerExplain production model drop to a PM
This question evaluates a candidate's ability to explain production model degradation, translate technical diagnostics into non-technical language, and articulate trade-offs between user impact and delivery timelines.
Behavioral & LeadershipTechnical Screen - ClickhouseMediumData EngineerAnswer SQL And Data Warehouse Fundamentals For A Data Engineering Interview
This problem tests foundational knowledge of SQL set operations, performance optimization techniques for join operations, and the architectural principles behind building scalable data warehouses.
Data Manipulation (SQL/Python)Technical ScreenSQLData WarehousingWindow Functions - DRWEasyData EngineerCompute a Year-End Balance with Monthly Card Fees
This problem tests logic implementation and data structure traversal, requiring the integration of conditional logic (fee waivers) into a sequential processing pipeline.
Coding & AlgorithmsOnline AssessmentData ProcessingLogicAggregation - DRWEasyData EngineerDelete the Fewest Characters to Avoid Triple Repeats
This problem tests string manipulation, greedy algorithm logic, and the ability to track character frequency counts to identify and prune violations of a constraint.
Coding & AlgorithmsOnline AssessmentStringsGreedyArrays - DRWEasyData EngineerImplement Nested Transactions in an In-Memory Database
This problem tests your ability to manage state and scope using stacks and dictionaries to implement transaction isolation in a key-value store.
Coding & AlgorithmsOnline AssessmentHash MapStackTransactions - DRWEasyData EngineerValidate a Password Against Explicit Security Rules
This problem tests string manipulation, character set validation, and the ability to apply a sequence of conditional checks efficiently.
Coding & AlgorithmsOnline AssessmentStringsValidationIteration - DatabricksMediumData EngineerDiagnose data quality and pipeline performance issues
Diagnose data quality and pipeline performance issues 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 - DiscordHardData EngineerDesign Video Call Analytics Tables
This question evaluates data modeling and analytics competencies including event schema design, dimensional modeling (facts and dimensions), ETL/cleaning and deduplication, and time-windowed SQL aggregation.
System DesignOnsite - 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 - 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 - DisneyMediumData EngineerDesign a clickstream ingestion and aggregation pipeline for billions of events per day
Design an end-to-end clickstream pipeline that ingests roughly one billion telemetry events per day from web, mobile, and TV clients and serves both near-real-time dashboards and accurate finalized daily aggregates without lagging. The question covers staged architecture and back-of-envelope sizing, a durable partitioned log for back-pressure, event-time windowing with watermarks and allowed lateness, late-arriving data and the provisional-to-finalized lifecycle, exactly-once deduplication in Flink versus Spark Structured Streaming, autoscaling on consumer lag, hot-partition key skew, high-cardinality DAU/MAU with HyperLogLog, and reprocessing after a logic bug. A common Disney data engineer online assessment system design question.
System DesignOnline Assessment - DisneyMediumData EngineerGenerate All Valid Combinations of Balanced Parentheses
This question tests a candidate's ability to apply recursive backtracking and combinatorial generation in a coding interview context. It evaluates understanding of constraint-based enumeration and string construction, core algorithmic skills frequently assessed in software engineering and data engineering roles.
Coding & AlgorithmsOnline Assessment - DisneyMediumData EngineerGenerate All Well-Formed Parenthesis Strings
This question tests practical understanding of recursion and backtracking through enumeration of all valid parenthesis combinations of a given length. It is a classic coding interview problem that evaluates combinatorial reasoning, constraint-based pruning, and familiarity with Catalan number sequences in algorithm design.
Coding & AlgorithmsOnline Assessment - 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 - FigmaMediumData EngineerWrite SQL for first share and closest collaborator
This question evaluates SQL proficiency—specifically joins, filtering, type casting, temporal aggregation, window functions or deduplication, and deterministic tie-breaking—by requiring derivation of first non-creator view times and per-creator collaborator counts from event tables.
Coding & AlgorithmsTechnical Screen - FigureaiMediumData EngineerBuild a Firmware Data Quality and Release-Feedback Framework
This question tests the ability to design an end-to-end data pipeline architecture that ensures high-fidelity telemetry collection, automated quality validation, and safe release orchestration for embedded firmware devices.
System DesignTechnical ScreenData EngineeringFirmwareObservability - FigureaiMediumData EngineerChoose a Metric Hierarchy for a Humanoid-Robot Fleet
This problem tests the ability to structure a multi-layered metrics dashboard for complex hardware-software systems, balancing operational efficiency against safety and system stability.
Analytics & ExperimentationTechnical ScreenMetricsData ModelingRobotics - FigureaiMediumData EngineerDesign a Telemetry Platform Ingesting Two Gigabytes per Second
This question tests your ability to design a high-throughput, fault-tolerant telemetry ingestion pipeline capable of handling high-velocity data streams from distributed robotic systems.
System DesignTechnical ScreenData EngineeringScalabilityDistributed Systems - FigureaiMediumData EngineerDiagnose the Leading Cause of Slow or Failed Charging
This problem tests your ability to define metrics from imperfect telemetry, perform root cause analysis on hardware failure, and design a strategy to identify performance bottlenecks in an autonomous charging system.
Analytics & ExperimentationTechnical ScreenData EngineeringRoot Cause AnalysisTelemetry - GoogleMediumData EngineerDescribe building and improving a dashboard
Prepare a Google Data Engineer behavioral answer about building and improving a stakeholder dashboard. The solution covers business goals, KPI design, data validation, BI tooling, anomaly detection, root-cause analysis, feedback handling, and measurable impact.
Behavioral & LeadershipTechnical Screen - GoogleMediumData EngineerUser Activity Analytics: Unique Users per Activity and Average Time on Site
This question evaluates a candidate's ability to process semi-structured event data using grouping, deduplication, and timestamp arithmetic in Python. It falls under coding and algorithms, commonly asked to assess practical data-wrangling skills such as aggregating per-key counts and computing time-based metrics while handling edge cases like unordered records and single-event users.
Coding & AlgorithmsTechnical Screen - GoogleMediumData EngineerWrite SQL and merge linked lists
Solve a SQL customer order aggregation task and merge two sorted linked lists. The solution uses CTEs, window functions, LEFT JOINs, COALESCE, latest-order tie handling, optional returned-order filtering, and an O(m+n) dummy-head linked-list merge.
Coding & AlgorithmsTechnical Screen - Interactive BrokersMediumData EngineerCompute Minimum Production Days
A data engineering coding screen on greedy scheduling under a cooldown constraint: produce an ordered list of products, one per day, where each product type must cool down for `space` days before it can be produced again. Candidates must return the minimum number of days, ideally in O(n) time using a hash map of last-produced days.
Coding & AlgorithmsTechnical Screen - Jain GlobalMediumData EngineerBuild a Self-Service Market Data Discovery and Support Layer
This problem tests your ability to design a robust metadata-driven orchestration layer that manages data lineage, access control, and quality monitoring for financial market datasets.
Software Engineering FundamentalsTechnical ScreenSystem DesignData EngineeringMetadata - Jain GlobalMediumData EngineerDesign an Incremental Rolling-Metrics Data Pipeline
Design an incremental batch data pipeline to compute multi-horizon rolling financial metrics over daily ticker observations, handling bounded historical restatements, atomic publication, and data reconciliation.
System DesignTechnical ScreenData EngineeringData PipelinesFinancial Data - Jain GlobalMediumData EngineerDesign and Debug a Point-in-Time Backtest Data Pipeline
This problem tests the ability to architect a robust financial data pipeline that ensures point-in-time accuracy and reproducible research.
System DesignTechnical ScreenData EngineeringFinancial DataBacktesting - Jain GlobalMediumData EngineerModel Effective-Dated Compliance Restrictions for Securities
This question tests the ability to design a time-series database schema capable of handling bitemporal data, identifier changes, and overlapping compliance restrictions.
System DesignTechnical ScreenData ModelingTime-SeriesBitemporal - LinkedInMediumData EngineerImplement a stack supporting max and popMax
This question evaluates understanding of data structures and algorithmic complexity, focusing on designing a stack variant that supports efficient retrieval and removal of the current maximum while preserving stack behavior.
Coding & AlgorithmsTechnical Screen - MetaHardData EngineerCompute Max Score From Up to 3 Categories
This Coding & Algorithms question in the Data Engineer domain evaluates grouping and top‑k aggregation concepts, testing the ability to combine per-category aggregation with selection under a uniqueness constraint.
Coding & AlgorithmsTechnical Screen - MetaMediumData EngineerCompute capacities after site closures
This question evaluates a candidate's ability to manipulate nested dictionary data structures and perform aggregate capacity computations, assessing data transformation, mapping, and set-based reasoning skills relevant to a Data Engineer within the Coding & Algorithms domain.
Coding & AlgorithmsTechnical Screen
Capital One
DRW
Databricks
Discord
Disney
Figma
Google
LinkedIn
Meta