Data Engineer Interview Questions

Data Engineer Interview Questions

Practice 160 real Data Engineer interview questions for 2026. Covers companies like Meta, TikTok, RBC Royal Bank, and Point72 — real questions from actual interviews with detailed solutions. This collection of Data Engineer interview questions is designed for hands‑on interview preparation: expect live SQL and Python exercises, pipeline design and debugging, and case problems that test data modeling, throughput and latency tradeoffs. What’s distinctive about data engineering interviews is the mix of coding plus systems thinking: interviewers evaluate SQL fluency and data modeling, end‑to‑end pipeline architecture (streaming, Spark, Kafka) and data reliability/observability. Meta, TikTok, RBC Royal Bank, and Point72 are actively hiring for this role and commonly test scalable ETL design, warehouse/schema design and production reliability. To prepare, practice medium‑to‑hard SQL, build a few Spark/streaming exercises, sketch architecture tradeoffs for high‑throughput pipelines, and rehearse concise behavioral stories that show ownership and incident response.

160 Questions 40 Companies08.03.2026
Showing 20 results
Role
Apple logo
Apple
Hard
Data Engineer

Encode and Rebuild a Binary Tree

Design two functions for a binary tree: - encode(root) -> string - decode(data) -> root Each tree node contains an integer value and has up to two chi...

Coding & Algorithms
10
0
86 people solved
Apr 2, 2026
Meta logo
Meta
Medium
Data Engineer Locked

Define metrics and data model for product features

This question evaluates a candidate's product sense and data engineering competency, including defining core success metrics, designing dashboard visu...

System Design
16
0
131 people solved
Mar 1, 2026
Google logo
Google
Medium
Data EngineerIntern

Write SQL and merge linked lists

The technical interview included two coding-style tasks: a SQL analytics query and merging two sorted linked lists. Constraints & Assumptions - For SQ...

Coding & Algorithms
4
1
70 people solved
Mar 9, 2025
Meta logo
Meta
Hard
Data Engineer

Model entities for feed content and shares

Scenario You are designing the data model for a social app’s News Feed that shows multiple content types (text, image, short video). Users can interac...

System Design
22
0
154 people solved
Dec 1, 2025
Meta logo
Meta
Medium
Data Engineer

Tackle Python tasks under time pressure

In a 15-minute coding round, implement a small Python function or class to solve a well-scoped problem within about 5 minutes of coding. 1) State 1–2 ...

Data Manipulation (SQL/Python)
18
0
148 people solved
Sep 6, 2025
Bloomberg logo
Bloomberg
Medium
Data Engineer

Implement RotatingFileSink in hierarchy

You are given an existing Python 3.10 codebase with an abstract base class RecordSink (from abc import ABC, abstractmethod) that defines open() -> Non...

Software Engineering Fundamentals
11
1
82 people solved
Sep 6, 2025
Apple logo
Apple
Medium
Data Engineer Locked

Design TikTok Data Engineering Systems

This question evaluates data engineering competencies including scalable streaming ingestion, processing orchestration, data partitioning and failure ...

System Design
10
0
74 people solved
Jan 30, 2026
Zoox logo
Zoox
Medium
Data EngineerSenior+

Write Transaction Analytics SQL Queries

You are given a credit-card transaction dataset with the following tables. transactions | column | type | description | |---|---|---| | transaction_id...

Coding & Algorithms
0
0
9 people solved
Apr 11, 2026
XPeng logo
XPeng
Medium
Data Engineer

Compare Data Infrastructure Storage Choices

You are designing data infrastructure for an autonomous-driving company. Discuss the following storage and processing concepts and trade-offs: 1. In P...

Software Engineering Fundamentals
1
0
24 people solved
Apr 11, 2026
Netflix logo
Netflix
Hard
Data Engineer Locked

Design config rollout and click aggregation

This question evaluates system design and data engineering competencies, focusing on distributed systems, global configuration management, deployment ...

System Design
9
0
91 people solved
Dec 13, 2025
Netflix logo
Netflix
Hard
Data Engineer Locked

Explain concurrency and reliability tradeoffs

This question evaluates skills in concurrent programming (thread-safety, synchronization primitives, memory visibility and lazy initialization) and di...

Software Engineering Fundamentals
5
0
62 people solved
Dec 13, 2025
Discord logo
Discord
Hard
Data Engineer

Implement Game Metadata Lookups

You are given a list of game metadata records. Build an in-memory representation that can store each game's name, release date, platforms, genre, publ...

Coding & Algorithms
11
0
143 people solved
Apr 3, 2026
Otter.Ai logo
Otter.Ai
Medium
Data EngineerSenior+

Find Every Project with the Most Employees

The interview report explicitly identified the “Project with Most Employees” SQL exercise. Use the following self-contained PostgreSQL schema: `text e...

Data Manipulation (SQL/Python)
2
0
25 people solved
Apr 2, 2026
Otter.Ai logo
Otter.Ai
Medium
Data EngineerSenior+

Find the Highest-Paid Employee in Each Department

The interview report explicitly identified the “Department Highest Salary” SQL exercise. Use the following self-contained PostgreSQL schema: `text dep...

Data Manipulation (SQL/Python)
1
0
14 people solved
Apr 2, 2026
Databricks logo
Databricks
Medium
Data Engineer

Diagnose data quality and pipeline performance issues

Diagnose data quality and pipeline performance issues Scenario You are interviewing for a Data Solutions Architect role. A customer is using a cloud d...

Behavioral & Leadership
15
0
135 people solved
Jul 25, 2025
Meta logo
Meta
Hard
Data Engineer

Evaluate impact of short videos in feed

Scenario You work on a social app’s main News Feed. The team wants to introduce a short-form video module ("Reels") into the feed. Prompt 1. How would...

System Design
18
0
165 people solved
Dec 1, 2025
Tesla logo
Tesla
Medium
Data Engineer Locked

Write SQL Data Transformation Queries

This question evaluates proficiency in SQL data transformation and aggregation, testing competencies such as monthly-reset running totals, hierarchica...

Coding & Algorithms
5
0
41 people solved
May 4, 2026
Amazon logo
Amazon
Easy
Data Engineer

Solve Two String Problems

You are asked to solve the following two coding problems: 1. Unique Morse Code Transformations You are given an array of lowercase English words, word...

Coding & Algorithms
19
0
150 people solved
Feb 23, 2026
Disney logo
Disney
Medium
Data Engineer

Hiring-Manager Round: Project Ownership, Influence, Communication, and Setbacks

This is the hiring-manager video round for a data/software engineering role. The interviewer opens by asking you to walk through a recent project you ...

Behavioral & Leadership
1
0
22 people solved
Feb 20, 2026
Meta logo
Meta
Medium
Data Engineer

Define and analyze product metrics

Product Analytics Case: Short‑Form Video Feed Context: You are evaluating a short‑form video feed feature inside a large social app where users swipe ...

Analytics & Experimentation
9
1
62 people solved
Sep 6, 2025

Frequently Asked Questions

How difficult are Data Engineer interviews on this 160-question page in 2026?
Across 160 real Data Engineer interview questions the overall difficulty ranges from straightforward SQL and ETL troubleshooting to demanding system-design and reliability problems. Early-stage screens and take-home or online assessments typically emphasize SQL, data-modeling, and short Python or PySpark exercises at an easy-to-medium level; onsite technical rounds shift to medium-to-hard topics such as Spark optimization, streaming semantics, and distributed joins. Senior-level interviews add architecture, capacity planning, and SLA-driven tradeoffs that feel closer to a systems engineering loop. Expect lower tolerance for fuzzy answers and higher emphasis on production-readiness than many pure analytics interviews.
What does a typical Data Engineer interview process look like and where are these roles most common now?
Typical loops begin with a recruiter screen for fit and background, followed by an online assessment or take-home focused on SQL and pipeline coding, then two to four technical interviews and one behavioral or stakeholder round; senior roles add a system-design interview. Data Engineering roles appear across data-platform teams, ads and recommendations, analytics engineering, and finance/trading groups. Companies hiring heavily in 2026 include TikTok, Point72, Disney, and RBC, with recurring themes: TikTok emphasizes Hive/Spark and streaming at recommendation scale; Point72 focuses on low-latency market-data and reliability; Disney often asks about event-driven media pipelines and analytics; RBC centers on cloud data platforms, governance, and robust ETL.
How should I plan my prep timeline and what are realistic stage-by-stage timelines for interviews?
A realistic hiring timeline runs three to six weeks from first contact to offer in many companies. Stage-by-stage: recruiter screen within 1 week, online assessment or homework within 3–7 days, first technical rounds spread over 1–2 weeks, system-design or senior-technical round during week 2–3 if applicable, and a behavioral/stakeholder loop plus final decision in the following week. For preparation, plan a focused four-week plan: week one on core SQL and data-modeling, week two on PySpark/ETL and streaming basics, week three on system design and tradeoffs with a mock interview, and week four on behavioral stories, resume-to-project alignment, and polishing timed exercises.
What key technical subtopics should I master for Data Engineer interviews in 2026?
Master SQL fundamentals including joins, aggregation, window functions, common-table-expressions, and performance patterns such as predicate pushdown and partition pruning. Be fluent in data modeling for OLAP and event schemas, ETL/ELT design, and batch versus streaming tradeoffs including exactly-once semantics and watermarking. Know big-data engines (Spark, Flink), message buses (Kafka), and cloud warehouses or lakehouses (Snowflake, BigQuery, Databricks patterns). Also practice pipeline observability, testing and CI for data jobs, query optimization, and cost/latency tradeoffs; be prepared to reason about metadata, retention, and data governance.
What standout tips will improve my chances and what common pitfalls should I avoid?
Standout tips: bring concrete metrics and outcomes for projects, explain tradeoffs with cost and latency in mind, and walk interviewers through execution plans and failure modes. Use a recent incident or postmortem to show ownership, discuss monitoring and alerting, and demonstrate automated testing for data quality. Common pitfalls include skipping clarifying questions, glossing over late or duplicate data, ignoring observability, over-optimizing without measuring, and failing to quantify impact. Communicate clearly, write readable SQL in interviews, and always justify design choices relative to stakeholders and SLAs.

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