11 eBay SQL Interview Questions (Updated 2024)

At eBay, SQL is used all the damn time for analyzing customer behavior trends and managing product inventory databases. That's why eBay made an in-house SQL tool which has over 5,000 employee users. Because of this, it shouldn't surprise you that eBay often asks SQL interview questions during interviews for Data Analyst, Data Science, and BI jobs.

So, in case you're studying for a SQL Interview, here’s 11 eBay SQL interview questions to practice, which are similar to recently asked questions at eBay – able to answer them all?

11 eBay SQL Interview Questions

SQL Question 1: Highest Number of Products

Assume that you are given the table below containing information on various orders made by eBay customers. Write a query to obtain the user IDs and number of products purchased by the top 3 customers; these customers must have spent at least $1,000 in total.

Output the user id and number of products in descending order. To break ties (i.e., if 2 customers both bought 10 products), the user who spent more should take precedence.

user_transactions Table:

user_transactions Example Input:

Example Output:

This is the same question as problem #5 in the SQL Chapter of Ace the Data Science Interview!

Answer:

SELECT 
  user_id, 
  COUNT(product_id) AS product_num 
FROM user_transactions 
GROUP BY user_id 
HAVING SUM(spend) >= 1000 
ORDER BY product_num DESC, SUM(spend) DESC
LIMIT 3;

To solve this question, try this eBay SQL question within DataLemur's interactive SQL code editor:

SQL Question 2: Database Design for eBay Listing and Bidding System

The business case here is simulating the eBay listing and bidding system. We'd like to be able to keep track of users, the products they list for sale, and the bids that other users place on these products. Design the tables to model this system and write a SQL query to fetch the highest current bid for each active listing.

Let's start by identifying the tables we'll need:

1. users - Information about users.
2. listings - Information about the products that are listed for sale.
3. bids - Information about the bids made by users on the listed products.

Here are your example tables:

users Sample Input:

listings Sample Input:

bids Sample Input:

Answer:

Here is the SQL query to fetch the highest bid for each active listing:

SELECT b.listing_id, l.product_name, MAX(b.amount) AS highest_bid
FROM bids b
JOIN listings l ON b.listing_id = l.listing_id
WHERE l.active
GROUP BY b.listing_id, l.product_name
ORDER BY highest_bid DESC;

This query joins the listings and bids table on the listing_id and filters out the listings that are not active. The MAX function is used to find the highest bid for listings and they are grouped by the listing_id in order to display the highest bid per listing. The result set is ordered in descending order of the highest_bid.

SQL Question 3: What is a self-join?

A self-join is a type of join in which a table is joined to itself. To perform a self-join, you need to specify the table name twice in the FROM clause, and give each instance of the table a different alias. You can then join the two instances of the table using a JOIN clause, and use a WHERE clause to specify the relationship between the rows.

Self-joins are the go-to technique for any data analysis that involves pairs of the same thing, like identifying pairs of products that are frequently purchased together like in this Walmart SQL interview question.

For another example, say you were doing an HR analytics project and needed to analyze how much all eBay employees in the same department interact with each other. Here's a self-join query you could use to retrieve all pairs of eBay employees who work in the same department:

SELECT e1.name AS employee1, e2.name AS employee2
FROM ebay_employees AS e1
JOIN ebay_employees AS e2 ON e1.department_id = e2.department_id
WHERE e1.id <> e2.id;

This query returns all pairs of eBay employees who work in the same department, and excludes pairs where the employee's id is the same (since this would represent the same eBay employee being paired with themselves).

SQL Question 4: Filter and Analyze eBay Customer Activity

In eBay's customer database table 'activities', the 'activity_type' column distinguishes between different types of customer activities such as "VIEW", "BID", and "BUY". The goal of this question is to filter out the customers who have viewed a product after bidding on it, but have not yet purchased it. You need to write a query that returns the user_id, product_id and the timestamp of their last "VIEW" activity. Assume that the 'timestamp' column is of the type 'timestamp', and it records the exact time when the customer made the activity.

activities Example Input:

Expected Output:

Answer:

The SQL query for this problem would look like this:

SELECT t.user_id, t.product_id, MAX(t.timestamp) AS last_view
FROM (
    SELECT user_id, product_id, timestamp
    FROM activities
    WHERE activity_type = 'VIEW'
    AND user_id IN (
        SELECT user_id
        FROM activities
        WHERE activity_type = 'BID'
    )
    AND user_id NOT IN (
        SELECT user_id
        FROM activities
        WHERE activity_type = 'BUY'
    )
) t
GROUP BY t.user_id, t.product_id;

This query first creates a subquery table consisting of "VIEW" activities, but filters out any activity from the customers who have also made a "BID" and have not made a "BUY" activity. Then it groups this table by customer and product, and selects the latest "VIEW" timestamp for each group.

To solve a related problem on DataLemur's free online SQL coding environment, try this Facebook SQL Interview question:

SQL Question 5: What's the purpose of the FOREIGN KEY constraint?

A FOREIGN KEY is a field in a table that references the PRIMARY KEY of another table. It creates a link between the two tables and ensures that the data in the FOREIGN KEY field is valid.

Say for example you had sales analytics data from eBay's CRM (customer-relationship management) tool.

CREATE TABLE ebay_accounts (
    account_id INTEGER PRIMARY KEY,
    account_name VARCHAR(255) NOT NULL,
    industry VARCHAR(255) NOT NULL
);

CREATE TABLE opportunities (
    opportunity_id INTEGER PRIMARY KEY,
    opportunity_name VARCHAR(255) NOT NULL,
    account_id INTEGER NOT NULL,
    FOREIGN KEY (account_id) REFERENCES ebay_accounts(account_id)
);

In this example, the opportunities table has a foreign key field called account_id that references the "account_id" field in the ebay_accounts table (the primary key). This helps to link the data about each opportunity to the corresponding account information in the accounts table.

This makes sure the insertion of rows in the opportunities table that do not have corresponding entries in the ebay_accounts table. It also helps to enforce the relationship between the two tables and ensures that data is not deleted from the ebay_accounts table if there are still references to it in the opportunities table.

SQL Question 6: Average Bidding Price Per Category

Given the tables bids and items, write a SQL query to calculate the average bidding price for each category of items on eBay. The bids table stores all the bids made for an item while the items table contains details about the item including its category.

bids Example Input:

items Example Input:

Answer:

SELECT 
  i.category, 
  AVG(b.bid_price) AS average_bid_price
FROM 
  bids b
INNER JOIN 
  items i 
ON 
  b.item_id = i.item_id
GROUP BY 
  i.category

This SQL query first joins the bids table and the items table on item_id. Then, it groups the resulting table by the category column of the items table. The AVG function is used to calculate the average bid_price for each category. The result of this query would be a table that lists each category with its average bidding price.

To practice another question about calculating rates, try this TikTok SQL Interview Question within DataLemur's interactive SQL code editor:

SQL Question 7: Can you describe the difference between a clustered and a non-clustered index?

Here's an example of a clustered index on the transaction_id column of a table of eBay payments table:

CREATE CLUSTERED INDEX transaction_id_index
ON ebay_payments (transaction_id);

This creates a clustered index on the transaction_id column, which will determine the physical order of the data rows in the table.

Here is an example of a non-clustered index on the transaction_id column of the same table:

CREATE INDEX transaction_id_index
ON ebay_payments (transaction_id);

This will create a non-clustered index on the transaction_id column, which will not affect the physical order of the data rows in the ebay_payments table.

In terms of query performance, a clustered index is usually faster for searches that return a large number of records, while a non-clustered index is faster for searches that return a small number of records. However, updates to a clustered index are slower, as they require the data rows to be physically rearranged, while updates to a non-clustered index are faster, as they only require the index data structure to be updated.

SQL Question 8: Determining the Click-Through Conversion Rate for eBay

You're a data analyst at eBay and are tasked to calculate the click-through-conversion rate for the previous month. Click-through conversion rate is defined as the number of users that viewed a product and then added that product to their cart, divided by the total number of users that viewed the product.

To start, let's assume we have two tables: product_views and add_to_cart, structured as follows.

product_views Input:

add_to_cart Input:

Answer:

Since we need to calculate the click-through-conversion rate on a per product basis for the previous month, we can make use of sub-queries and the LEFT JOIN clause to get desired result.

Here is a PostgreSQL statement:

SELECT pv.product_id, 
       (CAST(num_converted_users AS DECIMAL) / num_total_users) AS conversion_rate
FROM
    (SELECT product_id, COUNT(DISTINCT user_id) as num_total_users
     FROM product_views
     WHERE DATE_PART('month', view_date) = DATE_PART('month', CURRENT_DATE) - 1
     GROUP BY product_id) pv
LEFT JOIN
    (SELECT product_id, COUNT(DISTINCT user_id) as num_converted_users
     FROM add_to_cart
     WHERE DATE_PART('month', add_date) = DATE_PART('month', CURRENT_DATE) - 1
     GROUP BY product_id) atc
ON pv.product_id = atc.product_id;

The rate is calculated as the number of distinct users who added the product to the cart (num_converted_users) after a view, divided by the total number of users that viewed the product (num_total_users). We use LEFT JOIN to also include the products that were viewed but not added to the cart.

SQL Question 9: Retrieving eBay Seller Information

As a part of the eBay data team, you are often asked to retrieve specific information from seller records. You are required to retrieve all the sellers from the city of 'San Francisco' and their sales records whose name starts with the letter 'A' or 'B'. For the purpose of this exercise, we are only considering the sellers table which has the columns: seller_id, seller_name, city and the sales table which consists of a record of the sales done by these sellers. The sales table has the columns: sale_id, seller_id, sale_date and amount.

sellers Example Input:

sales Example Input:

Answer:

Below is a PostgreSQL query to solve the problem statement:

SELECT s.seller_name, se.sale_date, se.amount 
FROM sellers s 
JOIN sales se ON s.seller_id = se.seller_id
WHERE s.city = 'San Francisco' AND (s.seller_name LIKE 'A%' OR s.seller_name LIKE 'B%')

This query first joins the sellers and sales tables together to get the combined record of sales by each seller. The WHERE clause then filters out the records where the city is 'San Francisco' and the seller's name begins with either 'A' or 'B'.

SQL Question 10: Give a few ways in SQL that you can identify duplicate records in a table?

One way to find duplicates is to use a GROUP BY clause and then use HAVING to find groups

SELECT column_name, COUNT(*) as dup_count
FROM table_name
GROUP BY column_name
HAVING dup_count > 1;

You could also use the EXISTS operator:

SELECT *
FROM table_name t1
WHERE EXISTS (SELECT 1 FROM table_name t2 WHERE t1.column_name = t2.column_name AND t1.id <> t2.id);

SQL Question 11: Find Total Sales and Average Sale Value Per Product

For this question, let's consider that eBay wants to find the total number of sales and the average sale value for each product. You will have to use both the Sales and Products tables for this analysis.

Here are the Sales and Products tables:

Sales Example Input:

Products Example Input:

Only consider sales for which sale_value is non-null.

Combine these two tables to provide your analysis.

Answer:

Here is the PostgreSQL SQL query that can be used to solve this problem:

SELECT p.product_name, 
       COUNT(s.sale_id) as total_sales, 
       AVG(s.sale_value) as avg_sale_value
FROM Sales s
JOIN Products p ON s.product_id = p.product_id
WHERE s.sale_value IS NOT NULL
GROUP BY p.product_name;

This SQL query first joins the Sales and Products tables together based on their common field product_id. The WHERE clause then excludes sales that have a null sale_value. Finally, it uses the GROUP BY statement with the aggregating functions COUNT and AVG to find the total sales and average sale value per product.

The result of this query would be a table where each row represents a product from the Products table, and the columns show the total number of sales and average sale value per product.

How To Prepare for the eBay SQL Interview

The best way to prepare for a SQL interview, besides making sure you have strong SQL fundamentals, is to practice a ton of real SQL questions that were asked in recent job interviews. Besides solving the earlier eBay SQL interview questions, you should also solve the 200+ SQL questions on DataLemur which come from companies like Facebook, Google and unicorn tech startups.

Each SQL question has multiple hints, full answers and most importantly, there's an interactive SQL code editor so you can instantly run your SQL query and have it checked.

To prep for the eBay SQL interview you can also be useful to solve interview questions from other tech companies like:

• Amazon SQL questions
• Pinterest SQL questions
• Facebook SQL questions
• TikTok SQL questions

In case your SQL query skills are weak, don't worry about jumping right into solving questions – strengthen your SQL foundations with this free SQL for Data Analytics course.

This tutorial covers things like RANK vs. DENSE RANK and CASE/WHEN statements – both of these pop up often in eBay interviews.

eBay Data Science Interview Tips

What Do eBay Data Science Interviews Cover?

For the eBay Data Science Interview, besides SQL questions, the other types of questions to prepare for are:

• Statistics and Probability Questions
• Python or R Coding Questions
• Open-Ended Data Case Studies
• ML Modelling Questions
• Behavioral Interview Questions

How To Prepare for eBay Data Science Interviews?

To prepare for eBay Data Science interviews read the book Ace the Data Science Interview because it's got:

• 201 interview questions sourced from Facebook, Google & startups
• a crash course covering SQL, AB Testing & ML
• over 900+ 5-star reviews on Amazon