Data Engineer Interview Questions
Practice 140 real Data Engineer interview questions for 2026. Covers companies like Meta, TikTok, Rbcroyalbank, Capital One, and Amazon — real Data Engineer interview questions from actual interviews with detailed solutions to help your interview preparation. Expect the loop to emphasize production-grade SQL, scalable ETL and pipeline design, distributed-processing tooling (Spark/Kafka), data modeling for analytics and OLAP, and data-quality/observability trade-offs alongside behavioral and product-sense conversations tied to metrics. What’s distinctive: hiring teams now prioritize shipping reliable pipelines and diagnosing failures in production over pure algorithmic puzzles, so you’ll be evaluated on writing efficient windowed SQL, designing fault-tolerant pipelines, choosing storage and partitioning strategies, and explaining trade-offs around latency, cost, and observability. To prepare, practice timed SQL and Python exercises, sketch end-to-end pipeline designs with concrete components (Airflow, Kafka, S3/BigQuery/Redshift), rehearse STAR stories about ownership and incident response, and run mock interviews that simulate debugging a broken pipeline under time pressure.
"I got asked a hardcore MCM DP question and I saw it on PracHub as well. Solved that question in 5 minutes. Without PracHub I doubt I could solve it in 5 hours. Though somehow didn't get hired, perhaps I guess I solved it too fast? /s"
"Believe me i'm a student here jn US. Recently interviewed for MSFT. They asked me exact question from PracHub. I saw it the night before and ignored it cause why waste time on random sites. I legit wanna go back and redo this whole thing if I had chance. Not saying will work for everyone but there is certainly some merit to that website. And i'm gonna use it in future prep from now on like lc tagged"
"10 years of experience but never worked at a top company. PracHub's senior-level questions helped me break into FAANG at 35. Age is just a number."
"I was skeptical about the 'real questions' claim, so I put it to the test. I searched for the exact question I got grilled on at my last Meta onsite... and it was right there. Word for word."
"Got a Google recruiter call on Monday, interview on Friday. Crammed PracHub for 4 days. Passed every round. This platform is a miracle worker."
"I've used LC, Glassdoor, and random Discords. Nothing comes close to the accuracy here. The questions are actually current — that's what got me. Felt like I had a cheat sheet during the interview."
"The solution quality is insane. It covers approach, edge cases, time complexity, follow-ups. Nothing else comes close."
"Legit the only resource you need. TC went from 180k -> 350k. Just memorize the top 50 for your target company and you're golden."
"PracHub Premium for one month cost me the price of two coffees a week. It landed me a $280K+ starting offer."
"Literally just signed a $600k offer. I only had 2 weeks to prep, so I focused entirely on the company-tagged lists here. If you're targeting L5+, don't overthink it."
"Coaches and bootcamp prep courses cost around $200-300 but PracHub Premium is actually less than a Netflix subscription. And it landed me a $178K offer."
"I honestly don't know how you guys gather so many real interview questions. It's almost scary. I walked into my Amazon loop and recognized 3 out of 4 problems from your database."
"Discovered PracHub 10 days before my interview. By day 5, I stopped being nervous. By interview day, I was actually excited to show what I knew."
"I recently cleared Uber interviews (strong hire in the design round) and all the questions were present in prachub."
"The search is what sold me. I typed in a really niche DP problem I got asked last year and it actually came up, full breakdown and everything. These guys are clearly updating it constantly."
Write SQL for library analytics
Given a library database, write SQL to answer the following: 1) Count the number of books that are currently not returned (i.e., still checked out) an...
Explain Pandas and SQL Basics
You are interviewing for a Data Engineer internship. Answer the following short data-manipulation questions: 1. In pandas, what is the difference betw...
Compute missing letters to form original string
Implement a function that, given two strings original and typed (typed is a misspelled/partial version of original), returns the number of additional ...
Design a scalable dimensional model
Design a Dimensional Model for Transactional Analytics (Concrete Example Included) You are building a star-schema in a cloud data warehouse for near r...
Solve library SQL and Python tasks
You are given a library domain. Assume these tables: - books(book_id, author_id, title) - authors(author_id, name) - copies(copy_id, book_id, conditio...
Differentiate pandas objects and SQL filters
Python (pandas) 1. What is the difference between a pandas Series and a pandas DataFrame? - Discuss structure (1D vs 2D), indexing, column labels, ...
Recommend friends-of-friends
Question Given a dictionary such as {A:[B,C], B:[C,D], C:[E]}, return for a user U all people followed by U’s followees but not already followed by U....
Validate carpool capacity
Question LeetCode 1094. Car Pooling – Given trips[i] = [numPassengers, start, end] and an integer capacity, return true if the vehicle can fulfill all...
Describe building and improving a dashboard
Describe a past project where you built a dashboard for business or product stakeholders. Explain the business goal, the audience, the metrics you cho...
Describe a data-heavy project
Behavioral/Technical: Data‑Heavy Project Deep Dive (Data Engineer) Describe one data‑heavy project from your resume. In your answer, cover the followi...
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 ...
Write PostgreSQL string-manipulation query
You are given a PostgreSQL table clickstream(session_id TEXT, page TEXT, query TEXT, ts TIMESTAMP). The page column contains full URLs like 'https://s...
Write Postgres string parsing and aggregation query
You are given a PostgreSQL table events(user_id TEXT, raw TEXT) where raw stores pipe-delimited key=value pairs, for example 'user=U1|country=US|ts=20...
Optimize SQL to minimize scans
Given a large analytics query, refactor it to minimize table scans. 1) Replace unnecessary CTEs that cause multiple scans with inline aggregations or ...
Compute reservation diff for largest member
Given copies(copy_id, reserved_by_member_id) and members(member_id, referred_by_member_id), find the member with the largest member_id. Return a singl...
Find customer with max rentals in consecutive weeks
You are given a table purchases(customer_id INT, purchase_date DATE, rented_copies INT). Consider only dates in calendar year 2024. Define a full week...
Return count and renewal percentage of unreturned good copies
Tables: copies(copy_id, condition), checkouts(copy_id, checkout_date, return_date, renewal_count). Write a single SQL query that returns one row with ...
Debug a Hive Query for DAU
You are given two Hive tables: users(user_id BIGINT, created_at TIMESTAMP) and events(user_id BIGINT, event_time TIMESTAMP, event_name STRING) PARTITI...
Implement classes within an abstract Python framework
You are given an existing Python codebase (~200 lines shown) that defines an abstract base class DataProcessor with abstract methods load(self), trans...
Solve three SQL problems (easy/medium/hard)
Answer the following SQL tasks of increasing difficulty: 1) Aggregation: Given Orders(order_id, customer_id, amount, order_date), return each customer...