11 DocuSign SQL Interview Questions (Updated 2024)

Updated on

March 2, 2024

At DocuSign, SQL is used day-to-day to get product insights around how customers are signing legal documents, and what bottlenecks they face. Due to SQL's popularity within DocuSign, they often ask SQL coding questions during interviews for Data Analyst, Data Science, and BI jobs.

So, to help you prepare for the DocuSign SQL interview, here’s 11 DocuSign SQL interview questions – how many can you solve?

11 DocuSign SQL Interview Questions

SQL Question 1: Identify VIP Users for DocuSign

Given a database that logs DocuSign user activities, write a SQL query to identify the VIP users. A VIP user is defined as a user who sends more than 100 documents for signature in the last 30 days.

Assume you have the following tables:

Example Input:
Example Input:


This query first creates a subquery that counts the number of 'sent_for_signature' activities for each user in the last 30 days. It then filters out the users who have sent more than 100 documents in this period. Finally, it joins the subquery with the users table to get the names of these VIP users. This strategy ensures that only the necessary information is included and the result is accurate and efficient.

To work on another SQL customer analytics question where you can code right in the browser and have your SQL code instantly executed, try this Walmart Labs SQL Interview Question: Walmart SQL Interview Question

SQL Question 2: Analyze Monthly Usage and Revenue

In this problem, we want to analyze DocuSign's monthly usage and revenue.

DocuSign's business mainly involves electronically signing and sending documents, right? Let's say DocuSign charges users based on the number of documents signed each month. As a data analyst, you are provided with two tables - 'users' and 'usage'. The 'users' table contains information about each user, including their subscription plan (let's say 'BASIC', 'PRO', 'ENTERPRISE'). The 'usage' table tracks the number of documents each user has signed per month.

Your task is to write a SQL query that calculates the total number of documents signed and total revenue for each month and subscription plan. Assume the 'BASIC' plan costs 10perdocument,thePROplancosts10 per document, the 'PRO' plan costs 8 per document, and the 'ENTERPRISE' plan costs $5 per document.

Example Input:
Example Input:


Here is the SQL code for the described scenario:

This query first performs a JOIN operation on the 'users' and 'usage' tables on the 'user_id' column. It then groups the result by 'month' and 'subscription_plan'. For each group, it calculates the total number of documents signed (using SUM) and the total revenue (using a SUM with a CASE statement to conditionally multiply the number of documents by the appropriate rate dependent on the subscription plan). The result is ordered by 'month'.

Pro Tip: Window functions are a popular SQL interview topic, so practice every window function problem on DataLemur

DataLemur Window Function SQL Questions

SQL Question 3: Can you explain the distinction between a correlated and a non-correlated sub-query?

A correlated sub-query is a sub-query that depends on the outer query and cannot be executed separately. It uses the outer query to filter or transform data by referencing a column from it, and the outer query uses the results of the inner query. In contrast, a non-correlated sub-query is independent of the outer query and can be executed on its own. It does not reference any columns from the outer query and is used to retrieve additional data needed by the outer query.

Here is an example of a correlated sub-query:

This query selects the and total sales of all DocuSign customers in the sales table whose are greater than the average of their own customer group. The sub-query in this case is correlated with the outer query, as it references the column from the outer query ().

Here is an example of a non-correlated sub-query:

The sub-query in this case is non-correlated, as it does not reference any columns from the outer query.

Performance-wise, correlated sub-queries are generally slower to execute, as they have to be re-evaluated for each row of the outer query, while non-correlated sub-queries are faster, as they only have to be executed once.

DocuSign SQL Interview Questions

SQL Question 4: Document Activity Analysis

As a data analyst for DocuSign, a leading company for electronic signatures and agreements, you are tasked with understanding the frequency of document activity by the users and the type of activities they are mostly engaged in. Given the tables , , and , design a SQL query that counts the number of each type of activity (, , ) for each document per month.

Here are the tables:




201101Sales Contract
202102Lease Agreement
203103Employment Contract


301201Viewed06/08/2022 00:00:00
302201Signed06/10/2022 00:00:00
303202Viewed06/18/2022 00:00:00
304203Shared07/26/2022 00:00:00
305202Signed07/05/2022 00:00:00


This query first joins with on the . It then groups by document details, month, and activity type to get a count of each type of activity (, , ) for each document per month. The function is used to extract the month from the activity date. The result is ordered by descending month, then document_id and activity_type for legibility.

SQL Question 5: What's a database view, and what's it used for?

A database view is a virtual table that is created based on the results of a SELECT statement, and provides you a customized, read-only version of your data that you can query just like a regular table.

Views in SQL can help you enforce data security requirements by hiding sensitive data from certain users, and can improve performance for some queries by pre-computing the results for an intermediate step and storing them in a view (which can be faster than executing the intermediate query each time). However, their read-only nature means that on any underlying update, the view has to be re-computed.

SQL Question 6: Filter Customer Transactions for Specific Conditions

As a Data Analyst at DocuSign, you have been asked to extract customer transaction data. The filtered data is for customers who have transacted more than once, the transaction amount is greater than $500, and the transactions were made within the last 30 days.

Please write a SQL query to make this report.

The table in the database is structured as follows:

Example Input:


This query filters the transaction records for the past 30 days and transaction amounts greater than $500. It groups the results by customer id, counting the number of transactions per customer and summing their total transaction amounts. The HAVING clause then removes any group (customer) with only one transaction.

SQL Question 7: What does do?

Similar to the and / operators, the PostgreSQL INTERSECT operator combines result sets of two or more statements into a single result set. However, only returns the rows that are in BOTH select statements.

For a concrete example, say you were on the Sales Analytics team at DocuSign, and had data on sales leads exported from both HubSpot and Salesforce CRMs in two different tables. To write a query to analyze leads created after 2023 started, that show up in both CRMs, you would use the command:

SQL Question 8: Find the average document sign time on DocuSign

Given the 'documents' and 'signEvents' tables, can you write a SQL query to find the average time it takes for a document to be signed, in hours, per document type? Assume that 'documents' table contains information about all documents, with their respective document ids and types. 'signEvents' table, on the other hand, tracks when a document was sent out and when it was signed.

Below are some example entries for the 'documents' and 'signEvents' tables:

Example Input:
Example Input:
1100Sent2022-04-01 08:00:00
2101Sent2022-04-01 12:00:00
3102Sent2022-04-01 14:30:00
4100Signed2022-04-01 10:00:00
5101Signed2022-04-01 15:00:00
6102Signed2022-04-01 15:30:00


This query first selects all documents and their sent and signed times. It then joins the result with the 'documents' table on 'document_id'. It calculates the average of the differences between 'signed_time' and 'sent_time', converting the result from seconds to hours, grouped by 'document_type'. This gives the average sign time in hours for each type of document.

To practice a very similar question try this interactive Amazon Server Utilization Time Question which is similar for requiring calculation of time intervals with respective event types or this Facebook Average Post Hiatus (Part 1) Question which is similar for deriving the average time between distinct events.

SQL Question 9: Analyzing Customer's Document Categories

Suppose DocuSign wants to understand the document types most frequently used by each customer.

There are two tables - and . The table has information about the customer - , , , , while the table has information about each document - , (who created the document), .

We need to write a SQL query that joins these two tables, creating a resultant table that contains the , , , , and the for each customer.

Example Input
Example Input


Here is the PostgreSQL query:

In the subquery, we group the table by and and count the number of documents in each category for each user. The function is used with to rank each group of categories for each user based on the count of documents. Then, this result is joined with the table on to get final the result.

Example Output:


Because joins come up so often during SQL interviews, try this interactive Snapchat JOIN SQL interview question: Snapchat SQL Interview question using JOINS

SQL Question 10: What does do in a SQL query?

In SQL, the operator combines the result of two or more SELECT statements into a single result set. Note that each statement within the UNION must have the same number of columns and the columns must have similar data types. The operator removes duplicates from the final result set. If you want to include duplicates in the final result set, you can use the operator instead.

Here's an example of using the UNION operator to combine the results of two SELECT statements that retrieve data from tables of DocuSign's Facebook ads and their Google ads:

This statement would return a combined result set of both Facebook and Google ads that have a spend greater than $500.

SQL Question 11: Calculate Weighted Average Ratings by Month and Document Type

DocuSign wants to understand the average customer ratings for each document type at a detailed level. The rating is on a scale of 1-5 for each document submitted by users. The data is stored in two tables; containing the document submission details and containing the user ratings. In order to give more importance to the documents having more number of pages, calculate the weighted average rating adjusted by the total number of pages for each document type each month.

The formula to calculate the weighted average rating is:

The table:


The table:



This PostgreSQL query first combines the and tables using the field. It then uses the function to get the month from the . The function is used to calculate the weighted average, keeping it to 2 decimal places. The result is grouped by the month () and and sorted accordingly.

How To Prepare for the DocuSign SQL Interview

The key to acing a DocuSign SQL interview is to practice, practice, and then practice some more! Beyond just solving the earlier DocuSign SQL interview questions, you should also solve the 200+ SQL questions on DataLemur which come from companies like FAANG and tech startups. DataLemur SQL Interview Questions

Each DataLemur SQL question has hints to guide you, fully explained answers along with a discussion board to see how others solved it and most importantly, there is an online SQL code editor so you can right in the browser run your SQL query answer and have it checked.

To prep for the DocuSign SQL interview you can also be helpful to practice interview questions from other tech companies like:

But if your SQL coding skills are weak, forget about going right into solving questions – strengthen your SQL foundations with this interactive SQL tutorial.

SQL interview tutorial

This tutorial covers SQL topics like removing NULLs and LEFT vs. RIGHT JOIN – both of which show up routinely in DocuSign SQL interviews.

DocuSign Data Science Interview Tips

What Do DocuSign Data Science Interviews Cover?

In addition to SQL interview questions, the other types of questions tested in the DocuSign Data Science Interview are:

DocuSign Data Scientist

How To Prepare for DocuSign Data Science Interviews?

The best way to prepare for DocuSign Data Science interviews is by reading Ace the Data Science Interview. The book's got:

  • 201 Interview Questions from tech companies like Google & Microsoft
  • A Refresher on Python, SQL & ML
  • Amazing Reviews (900+ reviews, 4.5-star rating)

Ace the Data Science Interview by Nick Singh Kevin Huo