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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
- Companies
- 11
- Topics
- 8
- Languages
Showing 1–24 of 24 results
- AirbnbMediumData EngineerCalculate the Median House Price in Each City
Tests your ability to compute grouped medians in PostgreSQL, properly handling even and odd row counts, duplicate price values, and numeric precision.
Data Manipulation (SQL/Python)Onsitesqlpostgresqlaggregations - AirbnbMediumData EngineerEstimate Page-Visit Duration from the Next User Event
Implement logic to compute user page-visit durations based on adjacent event timestamps, deterministically resolving ties and handling boundary conditions for terminal events.
Data Manipulation (SQL/Python)Onsitepythonsqldata-manipulation - AirbnbMediumData EngineerFind Hosts Meeting Listing, Rating, and Review-Coverage Rules
Tests the ability to write a SQL query performing multi-table aggregations, date-windowed conditional logic, and host-level qualification filtering across listing counts, average ratings, and recent review coverage.
Data Manipulation (SQL/Python)Onsitesqlaggregationconditional-logic - AirbnbMediumData EngineerFind Users with Seven Consecutive Impression Days
Tests your ability to identify consecutive calendar-day activity streaks in PostgreSQL using window functions, date arithmetic, and deduplication.
Data Manipulation (SQL/Python)Onsitesqlpostgresqlwindow-functions - ByteDanceMediumData EngineerConnect Points With Minimum Total Distance
This problem tests your ability to model a geometric optimization task as a Minimum Spanning Tree (MST) problem and implement it efficiently using Kruskal's or Prim's algorithm.
Coding & AlgorithmsOnsiteGraphsMSTGeometry - 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 - 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 - MetaHardData EngineerDefine and validate product metrics
Define and validate product metrics evaluates metric design, causal reasoning, experiment setup, diagnostics, SQL/statistical checks, and recommendations in a realistic interview setting. A strong answer states assumptions, handles edge cases, explains trade-offs, and shows how to validate the result clearly.
Analytics & ExperimentationOnsite - MetaHardData EngineerDesign batch and streaming ETL architecture
Design batch and streaming ETL architecture evaluates requirements, scale assumptions, API/data design, architecture, trade-offs, failure modes, and rollout in a realistic interview setting. A strong answer states assumptions, handles edge cases, explains trade-offs, and shows how to validate the result clearly.
System DesignOnsite - MetaHardData EngineerEvaluate impact of short videos in feed
This question evaluates competency in metrics definition, causal experimentation, product analytics, and feed system behavior within the System Design and Data Engineering domain.
System DesignOnsite - MetaMediumData EngineerRecommend two-hop follows in Python
This question evaluates fluency with graph traversal, set operations, deduplication, and frequency-based ranking in Python, targeting manipulation of directed "follows" relationships represented as dictionaries and is categorized under Data Manipulation (SQL/Python).
Data Manipulation (SQL/Python)Onsite - MetaMediumData EngineerReturn top-3 content per category
This question evaluates the ability to perform grouped top-k selection, deterministic tie-breaking and ordering, and to reason about algorithmic efficiency when manipulating structured datasets in the Data Manipulation (SQL/Python) domain for a Data Engineer role.
Data Manipulation (SQL/Python)Onsite - MetaMediumData EngineerValidate carpool capacity
This question evaluates understanding of interval-based resource accounting and algorithmic reasoning with cumulative constraints, assessing skills in processing time-bound events and managing capacity limits.
Coding & AlgorithmsOnsite - MetaMediumData EngineerVisualize Netflix metric trends
This interview question evaluates metric design, causal reasoning, experiment setup, diagnostics, SQL/statistical checks, and recommendations in a realistic interview setting. A strong answer for Visualize Netflix metric trends states assumptions, handles edge cases, explains trade-offs, and shows how to validate the result clearly.
Analytics & ExperimentationOnsite - MetaHardData EngineerWrite SQL for car rental utilization by city
This question evaluates proficiency in SQL querying and relational data modeling, focusing on time-interval overlap logic, distinct aggregation across joined tables, null handling, and safe computation of utilization metrics.
Coding & AlgorithmsOnsite - NetflixHardData EngineerDesign config rollout and click aggregation
This problem tests your ability to design a global configuration distribution system combined with a high-throughput event processing pipeline to monitor rollout health.
System DesignOnsiteDistributed SystemsReal-time AnalyticsEvent Streaming - NetflixHardData EngineerExplain concurrency and reliability tradeoffs
This problem tests your understanding of balancing thread-safe resource management in a high-concurrency local environment against the systemic requirements of a distributed data pipeline.
Software Engineering FundamentalsOnsiteConcurrencyDistributed SystemsCaching - NetflixHardData EngineerImplement phrase search and JSON path
This problem tests your ability to process unstructured text into a searchable index and navigate hierarchical data structures using path patterns.
Coding & AlgorithmsOnsiteInverted IndexString ProcessingRecursion - NotionMediumData EngineerExplain impact and partnership
This question evaluates a Data Engineer's behavioral and leadership competencies, including ownership, cross-functional collaboration with data scientists and partners, stakeholder communication, problem framing, impact measurement, and responsiveness to managerial feedback, and is categorized under Behavioral & Leadership.
Behavioral & LeadershipOnsite - ZooxMediumData EngineerDesign teleoperations data models and pipelines
This question evaluates competency in data modeling, real-time and batch pipeline architecture, telemetry ingestion, metrics design, and operational monitoring for teleoperations and autonomous vehicle stability.
System DesignOnsite - ZooxMediumData EngineerExplain seasons and compound interest
This question evaluates quantitative reasoning and basic scientific literacy by testing understanding of Earth's axial tilt and seasonal temperature variation alongside exponential growth and compound interest calculations.
Software Engineering FundamentalsOnsite - ZooxMediumData EngineerWrite SQL revenue and anomaly queries
This question evaluates SQL proficiency and data engineering competency in revenue aggregation, netting purchases and refunds, joining transaction and vendor tables, and designing data quality and anomaly detection checks.
Coding & AlgorithmsOnsite
Airbnb
Discord
Disney
Meta
Netflix
Notion
Zoox