Amazon Data Scientist Data Manipulation (SQL/Python) Interview Questions
Practice 48 real Data Manipulation (SQL/Python) interview questions for Data Scientist roles at Amazon.
"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"
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"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."
Append country tables and rank salaries in USD
You have separate country-level employee tables that must be appended and ranked by salary converted to USD using an exchange rate table. SQL schema a...
Find top-spend categories per customer with ranking
Using the schema and sample data below, write a single ANSI SQL query (CTEs allowed; no temp tables) that returns, for each customer, their top 2 prod...
Calculate Weekly, Monthly Hours Watched by Premium Users
watch_events +-----------+----------+----------------+-----------------------+----------------+ | user_id | video_id | watched_minutes| watched_at ...
Ensure Correct Numeric Ordering in Visit ID Comparison
visits +----------+---------+-----------+---------------------+ | visit_id | user_id | page | visit_ts | +----------+---------+-------...
Create Country-Level Spend Report Using Pandas
users +---------+---------+ | user_id | country | +---------+---------+ | 1 | US | | 2 | CA | | 3 | US | +---------+-...
Identify First Daily Order for Each Merchant
Orders +----------+-------------+---------+------------+ | order_id | merchant_id | amount | order_date | +----------+-------------+---------+-------...
Find recommended friend pairs by shared listening
Problem (SQL) You work on a music app and want to recommend new friend connections based on listening similarity. Tables Assume the following schemas:...
Find daily first-order merchants with SQL
Given the table below, write a single SQL query using window functions to: A) For each calendar date (UTC), return all merchant_id(s) whose order is t...
Design student–course data models and SQL
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Transform event logs with subscription windows in pandas
Using pandas, compute user-level subscription-aligned revenue and anomalies for September 2025. DataFrames: events(user_id:int, ts:UTC datetime, event...
Transform retail data with pandas groupby/merge/concat
Using pandas only (groupby/agg/merge/concat; no for-loops), write code to answer the sub-questions below on the following small dataframes. Assume tim...
Verify subscriptions and analyze orders with SQL/Python
You are given two tables. Write SQL and Python (pandas) to answer the sub-questions precisely, handling edge cases, ties, and missing data. Schema - s...
Compute daily work hours from in/out events
Given punch events, compute each employee’s daily hours, handling unmatched events and overnight shifts. Write SQL over: events(employee_id INT, evt_t...
Calculate cross-channel login user proportions
Write SQL to compute, for 2025-08-29 through 2025-08-31, the proportion of users who logged in only via mobile, only via desktop, and via both, where ...
Design SQL/Pandas aggregations on retail schema
Using the schema and sample data below, answer both parts. Assume today is 2025-09-01. Use standard SQL (e.g., PostgreSQL) and idiomatic pandas withou...
Understand SQL: DELETE vs TRUNCATE, VIEW vs TABLE, CROSS JOIN
employees +----+--------+---------+ | id | name | dept_id | +----+--------+---------+ | 1 | Alice | 10 | | 2 | Bob | 20 | | 3 | Car...
Analyze Top 10 Items' Revenue Contribution by Category
sales +----------+------------+---------+---------+------------+ | order_id | category | item_id | revenue | order_date | +----------+------------+-...
Explain MySQL to MS SQL Server query syntax differences.
transactions | id | user_id | amount | txn_date | |----|---------|--------|----------| | 1 | 1001 | 25.00 | 2023-07-01 | | 2 | 1002 | 40.00 ...
Analyze User Engagement with SQL Queries
events +----------+---------+---------------------+ | event_id | user_id | event_time | +----------+---------+---------------------+ | 1 ...
List Top Customers and Monthly Order Counts in SQL
Orders | order_id | customer_id | order_date | amount | |----------|-------------|------------|--------| | 1 | 101 | 2023-01-05 | 120.5...