Topic – Amazon Business Intelligence Interview Questions
Company – Amazon
Designation – Business Intelligence Engineer I
Compensation – 15 – 20 LPA Fixed + 5 – 9 Lakhs JB + $40k – $80K worth of stocks for 4 years
Location – Bangalore
Experience Required – Freshers to 5 YOE
Technical Skills required – Advanced SQL, Basic Python, Case Study, Amazon 14 Principle,s and Visualization in any tool like Tableau/Power BI

Amazon Business Intelligence Interview Questions

Amazon Business Intelligence Interview Questions SQL

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Get 200+ Most Asked and Advance SQL Interview Questions to crack ANY analytics Interview

1. Find the customer(s) who placed the most orders.
2. Show cumulative sales per month.

SELECT
order_month,
SUM(sales) OVER (ORDER BY order_month) AS cumulative_sales
FROM monthly_sales;

3. What is each employee’s sales as a % of total sales?

4. Count distinct users logging in each day.

SELECT
login_date,
COUNT(DISTINCT user_id) AS daily_active_users
FROM logins
GROUP BY login_date;

5. Find all users who signed up more than once with the same email.

6. Show number of orders each month and the month-over-month change.

SELECT
TO_CHAR(order_date, ‘YYYY-MM’) AS month,
COUNT() AS orders, COUNT() – LAG(COUNT(*)) OVER (ORDER BY TO_CHAR(order_date, ‘YYYY-MM’)) AS mom_change
FROM orders
GROUP BY TO_CHAR(order_date, ‘YYYY-MM’);

7. Get the product that generated the highest revenue.

8. Find how many users came back after signing up in the previous week.

WITH signup AS (
SELECT user_id, MIN(login_date) AS signup_date
FROM logins
GROUP BY user_id
),
retention AS (
SELECT l.user_id
FROM logins l
JOIN signup s ON l.user_id = s.user_id
WHERE l.login_date > s.signup_date
)
SELECT COUNT(DISTINCT user_id) AS returning_users FROM retention;

9. Get the most recent order for each customer.

SELECT *
FROM (
SELECT *,
ROW_NUMBER() OVER (PARTITION BY customer_id ORDER BY order_date DESC) AS rn
FROM orders
) latest
WHERE rn = 1;

Amazon Python Interview Questions

You will get answers to all the relevant questions asked in ANY Ananlytics interview across topics like SQL, Python, Pandas, Numpy, 6 ML Algorithms, Hadoop, Terminal Commands, Big Data Technologies, Power BI, Statistics, MS Excel and many more in our:

2200+ Interview Questions to Become a Full Stack Analytics Professional

1. How do you read a CSV file into a pandas DataFrame and display the first 5 rows?

import pandas as pd

df = pd.read_csv(‘file.csv’)
print(df.head())

2. Given a DataFrame with department and salary, find the average salary per department.

df.groupby(‘department’)[‘salary’].mean()

3. How do you check for missing values and fill them with the column mean?

4. How do you categorize ages into groups (e.g., Youth, Adult, Senior)?

5. Identify outliers using the IQR method.

Q1 = df[‘salary’].quantile(0.25)
Q3 = df[‘salary’].quantile(0.75)
IQR = Q3 – Q1

outliers = df[(df[‘salary’] < Q1 – 1.5IQR) | (df[‘salary’] > Q3 + 1.5IQR)]

6. What’s the difference between merge() and join() in pandas?

7. Convert all values in a column to lowercase and strip whitespaces.

8. Convert a string column to datetime and extract the month.

9. Create a 3×3 matrix with values from 1 to 9.

import numpy as np
matrix = np.arange(1, 10).reshape(3, 3)

10. You’re given a DataFrame with user_id, timestamp, and activity. How do you find the first activity of each user?

df.sort_values(by=[‘user_id’, ‘timestamp’], inplace=True)
first_activity = df.groupby(‘user_id’).first().reset_index()

Amazon Case Study and 14 Principles Interview Questions

Case Study Questions

We have covered 120+ Case Studies asked in Microsoft, Apple, Amazon,Facebook, NVIDIA, Amazon 14 principles, MakeMyTrip, Uber, Intel, Salesforce, CISCO and Web Analytics KPIs. If you are specifically looking forward to strengthen your Case Study skills, then you should definitely Go for the below books

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Scenario: You’re given data for Prime Day sales across categories. Leadership wants to know which category underperformed and why.

Q: What steps would you take to analyze this? What metrics would you focus on? How would you communicate your findings?

Scenario: You notice a drop in Prime user engagement in the last quarter.

Q: How would you identify the cause of churn? What data sources would you analyze? How would you measure the success of your recommendation?

Scenario: There’s an uptick in delivery delays in the Midwest.

Q: What data would you look at? How would you confirm if it’s a systemic issue or isolated to certain hubs? How do you escalate?

Amazon 14 Leadership Principles Questions

Go through The Data Monk’s Youtube video on 14 Amazon Principles and How to solve these questions with example – Amazon 14 Leadership Principles


Q: Tell me about a time you went above and beyond to meet customer expectations.

Q: Describe a situation where you found a root cause that others missed.

Q: Share an example when you had a tight deadline and how you delivered despite challenges.

Q: Tell me about a time you disagreed with your manager or a stakeholder. What happened?

Q: Give an example when you took a calculated risk without having all the data. What was the result?

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