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

Discuss Challenges and Career Goals

Answer the following behavioral interview questions: 1. What was the most difficult problem you have faced in your work, and how did you approach it? ...

Behavioral & Leadership
23
0
207 people solved
Apr 2, 2026
BlackRock logo
BlackRock
Medium
Data Engineer

Solve two interval array problems

You are given two interval-based tasks from a technical screen for a data engineering role. 1. Merge overlapping intervals - Input: an array of int...

Coding & Algorithms
7
0
78 people solved
Feb 18, 2026
Amazon logo
Amazon
Easy
Data EngineerIntern

Answer Amazon Behavioral Questions

Question You are in the behavioral portion of an Amazon final-round interview (Software Development Engineer internship). Prepare strong, structured r...

Behavioral & Leadership
21
0
269 people solved
Feb 23, 2026
Figma logo
Figma
Medium
Data Engineer

Write SQL for first share and closest collaborator

You are given event data about users viewing design files. Assume the following tables: - files(file_id, creator_id) - creator_id is a VARCHAR user ...

Coding & Algorithms
34
0
287 people solved
Jan 20, 2026
Akuna Capital logo
Akuna Capital
Medium
Data Engineer Locked

Write February Resource Usage Query

This question evaluates SQL competency in aggregation, group-level filtering, time-range handling for DATE/TIMESTAMP values, and combining results fro...

Software Engineering Fundamentals
8
0
65 people solved
May 30, 2026
Meta logo
Meta
Medium
Data Engineer

Solve SQL and Python coding tasks

You are given a small library system with the following relational schema and several Python data-processing tasks. Answer the SQL questions and imple...

Coding & Algorithms
61
5
415 people solved
Nov 20, 2025
Rbcroyalbank logo
Rbcroyalbank
Easy
Data EngineerIntern

Describe ETL and pipeline challenges

Question You are interviewing for a Data Engineer co-op / intern role at RBC (Royal Bank of Canada). The technical screen is a set of resume-based and...

Behavioral & Leadership
13
0
110 people solved
Jan 14, 2026
Nextdoor logo
Nextdoor
Hard
Data Engineer

Design KPI dashboard tables: retention, weekly rollups, timezone

Question You are designing the analytical data model behind a fast KPI dashboard for a large-scale photo-sharing app. The dashboard is reported daily ...

System Design
13
0
107 people solved
Feb 8, 2026
Zoox logo
Zoox
Medium
Data Engineer

Explain seasons and compound interest

Answer the following basic reasoning questions: 1. Why is summer generally hotter than winter? 2. Suppose you invest $1,000 at a 100% annual interest ...

Software Engineering Fundamentals
7
0
105 people solved
Apr 4, 2026
Figureai logo
Figureai
Medium
Data EngineerSenior+ Locked

Explain How AI Changes Data Engineering Work

Explain how AI-assisted tools could reshape data engineering while preserving human accountability. Cover risk-based task boundaries, privacy, indepen...

Behavioral & Leadership
2
0
14 people solved
May 20, 2026
Capital One logo
Capital One
Medium
Data Engineer

Evaluate credit-limit increase profitability

Business/Analytics Case: Credit Limit Increase Strategy You are a data scientist supporting a consumer credit business. Scenario The company is consid...

System Design
18
0
209 people solved
Mar 1, 2026
Notion logo
Notion
Medium
Data Engineer Locked

Design an event analytics platform

This question evaluates a candidate's skills in data engineering and system design for event analytics, covering platform architecture, data ingestion...

System Design
18
0
188 people solved
Apr 10, 2026
Zoox logo
Zoox
Medium
Data EngineerSenior+

Design Transaction Data Quality Checks

You own data quality for the same credit-card transaction dataset. transactions | column | type | description | |---|---|---| | transaction_id | integ...

Software Engineering Fundamentals
3
0
60 people solved
Apr 11, 2026
Disney logo
Disney
Medium
Data Engineer

Hiring Manager Behavioral Round: Project Impact, Influence, Communication, and Setbacks

Hiring Manager Behavioral Round: Project Impact, Influence, Communication, and Setbacks This is a hiring-manager video round centered on your project ...

Behavioral & Leadership
1
0
21 people solved
Mar 27, 2026
LinkedIn logo
LinkedIn
Medium
Data EngineerSenior+

Implement a stack supporting max and popMax

Design a data structure that behaves like a stack but also supports retrieving and removing the current maximum value. Implement a class MaxStack with...

Coding & Algorithms
8
0
77 people solved
Feb 2, 2026
Notion logo
Notion
Medium
Data Engineer

Explain impact and partnership

Prepare for a hiring manager interview and a cross-functional partner conversation. Be ready to answer questions such as: - Why do you want to join th...

Behavioral & Leadership
10
0
105 people solved
Apr 10, 2026
xAI logo
xAI
Medium
Data Engineer

Design a schema for server engagement

You are building analytics for a chat platform similar to Discord. The raw event sources are: - server(server_id, creator_id, created_at) - server_vie...

System Design
14
0
112 people solved
Jan 17, 2026
Nextdoor logo
Nextdoor
Hard
Data Engineer

Write SQL for basic user metrics

You are given a simplified schema for a fictional social app called Nextagram: - users(user_id PK, username, created_at TIMESTAMP) - follows(follower_...

Coding & Algorithms
5
0
88 people solved
Feb 8, 2026
Zoox logo
Zoox
Medium
Data Engineer

Write SQL revenue and anomaly queries

You are given two tables. Table: transactions | Column | Type | Description | |---|---|---| | transaction_id | int | Unique identifier for each transa...

Coding & Algorithms
4
0
63 people solved
Apr 4, 2026
Meta logo
Meta
Hard
Data Engineer

Design batch and streaming ETL architecture

Design batch and streaming ETL architecture System Design: End-to-End Data Platform for Product Analytics (Batch + Near-Real-Time) Context Design a sc...

System Design
67
0
511 people solved
Jul 15, 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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