11 Vanguard SQL Interview Questions (Updated 2024)
At Vanguard, SQL is used for analyzing financial datasets for predictive insights and managing data warehousing for data integrity. That's why Vanguard often tests SQL coding questions in interviews for Data Science and Data Engineering positions.
Thus, to help you prep for the Vanguard SQL interview, here’s 11 Vanguard SQL interview questions can you solve them?
11 Vanguard SQL Interview Questions
SQL Question 1: Identifying High Net Worth Clients
Vanguard is an investment management company, hence the 'power users' in this case could be the High Net Worth (HWN) clients who invest large sums of money in Vanguard's various investment products. Write a SQL query to identify the top 10 clients who invested the highest total amount in 2022.
Sample tables are provided below with some mock data. Use these tables to frame your query.
Example Input:
| client_id | name |
|---|---|
| 100 | Abby Johnson |
| 101 | Warren Buffet |
| 102 | Charlie Munger |
| 103 | Peter Lynch |
| 104 | George Soros |
Example Input:
| invest_id | client_id | investment_date | product_id | investment_amount |
|---|---|---|---|---|
| 6171 | 100 | 01/10/2022 | 50001 | $30000 |
| 7802 | 101 | 02/10/2022 | 50002 | $50000 |
| 5293 | 102 | 03/10/2022 | 50001 | $100000 |
| 6352 | 103 | 04/10/2022 | 50002 | $45000 |
| 4517 | 104 | 05/10/2022 | 50002 | $70000 |
Answer:
The following PostgreSQL query should generate the required results:
This query first joins the two tables, and , on the field. It then filters for investment records from the year 2022. The clause groups the remaining records by client, and for each client, calculates the sum of their investment amounts. This total investment is then ordered in descending order to list the clients who have invested the most, and the clause retrieves only the top 10 records.
To work on another SQL customer analytics question where you can code right in the browser and have your SQL solution automatically checked, try this Walmart SQL Interview Question:
SQL Question 2: Top 3 Department Salaries
Assume there was a table of Vanguard employee salary data. Write a SQL query to find the top three highest paid employees in each department.
Vanguard Example Input:
| employee_id | name | salary | department_id |
|---|---|---|---|
| 1 | Emma Thompson | 3800 | 1 |
| 2 | Daniel Rodriguez | 2230 | 1 |
| 3 | Olivia Smith | 2000 | 1 |
| 4 | Noah Johnson | 6800 | 2 |
| 5 | Sophia Martinez | 1750 | 1 |
| 8 | William Davis | 6800 | 2 |
| 10 | James Anderson | 4000 | 1 |
Example Input:
| department_id | department_name |
|---|---|
| 1 | Data Analytics |
| 2 | Data Science |
Example Output:
| department_name | name | salary |
|---|---|---|
| Data Analytics | James Anderson | 4000 |
| Data Analytics | Emma Thompson | 3800 |
| Data Analytics | Daniel Rodriguez | 2230 |
| Data Science | Noah Johnson | 6800 |
| Data Science | William Davis | 6800 |
Test your SQL query for this interview question and run your code right in DataLemur's online SQL environment:
Answer:
We use the DENSE_RANK() window function to generate unique ranks for each employee's salary within their department, with higher salaries receiving lower ranks. Then, we wrap this up in a CTE and filter the employees with a ranking of 3 or lower.
If the code above is hard to understand, you can find a step-by-step solution with hints here: Top 3 Department Salaries.
Read about the Data & Analytics team at Vangaurd and how they prioritize continous learning.
SQL Question 3: How can you select records without duplicates from a table?
The keyword added to a statement can be used to get records without duplicates.
For example, say you had a table of Vanguard customers:
| name | city |
|---|---|
| Akash | SF |
| Brittany | NYC |
| Carlos | NYC |
| Diego | Seattle |
| Eva | SF |
| Faye | Seattle |
Suppose you wanted to figure out which cities the customers lived in, but didn't want duplicate results, you could write a query like this:
Your result would be:
| city |
|---|
| SF |
| NYC |
| Seattle |
SQL Question 4: Average Investment Returns by Product
Vanguard is a company known for its investment products. One possible dataset they might have is tracking the monthly return percentage for different financial products.
Here, we want to find the average return percentage for each product over the trailing 3-month period, in each month. Assume the return percentages are calculated at the end of each month.
For simplicity, ignore months where there is fewer than 3 months of historical data available.
Example Input:
| id | year | month | product_id | return_percentage |
|---|---|---|---|---|
| 1 | 2022 | 1 | 10 | 2.34 |
| 2 | 2022 | 1 | 20 | 1.90 |
| 3 | 2022 | 2 | 10 | 2.50 |
| 4 | 2022 | 2 | 20 | 2.10 |
| 5 | 2022 | 3 | 10 | 3.00 |
| 6 | 2022 | 3 | 20 | 2.50 |
| 7 | 2022 | 4 | 10 | 2.25 |
| 8 | 2022 | 4 | 20 | 2.20 |
| 9 | 2022 | 5 | 10 | 1.90 |
| 10 | 2022 | 5 | 20 | 2.30 |
Example Output:
| year | month | product_id | avg_return_percentage |
|---|---|---|---|
| 2022 | 3 | 10 | 2.61 |
| 2022 | 3 | 20 | 2.17 |
| 2022 | 4 | 10 | 2.58 |
| 2022 | 4 | 20 | 2.27 |
| 2022 | 5 | 10 | 2.38 |
| 2022 | 5 | 20 | 2.33 |
Answer:
This SQL query uses the window function to calculate the average return percentage over the current row and the two preceding rows, partitioned by each product. Note that the window frame is defined as "ROWS BETWEEN 2 PRECEDING AND CURRENT ROW", meaning it covers a 3-month span including the current month and the two previous months. The ordering is crucial in this problem to ensure the window frame spans over consecutive months. We sort the data by year, month, and product_id to obtain a more readable result. After the window function is applied, we sort the results by year, month, and product_id. This provides the average 3-month trailing return percentage for each product in each month.
To solve another window function question on DataLemur's free interactive coding environment, try this Amazon SQL question asked in a BI Engineer interview:
SQL Question 5: How do cross joins and natural joins differ?
Cross joins and natural joins are two types of JOIN operations in SQL that are used to combine data from multiple tables. A cross join creates a new table by combining each row from the first table with every row from the second table, and is also known as a cartesian join. On the other hand, a natural join combines rows from two or more tables based on their common columns, forming a new table. One key difference between these types of JOINs is that cross joins do not require common columns between the tables being joined, while natural joins do.
Here's an example of a cross join:
If you have 20 products and 10 colors, that's 200 rows right there!
Here's a natural join example using two tables, Vanguard employees and Vanguard managers:
This natural join returns all rows from Vanguard employees where there is no matching row in managers based on the column.
SQL Question 6: Filter Customer Records with Multiple Conditions
At Vanguard, we have a database of our customer records. We are particularly interested in customers who live in New York ("NY") or California("CA"), are active and have at least $100,000 in their accounts. Write a SQL query to obtain these records from our customer database.
Example Input:
| customer_id | first_name | last_name | state | account_status | account_balance |
|---|---|---|---|---|---|
| 1050 | John | Doe | NY | active | 105500 |
| 2050 | Jane | Smith | CA | inactive | 205000 |
| 3050 | Sam | Green | NY | active | 305000 |
| 4050 | Betty | Brown | TX | active | 405000 |
| 5050 | Bob | Johnson | CA | active | 50500 |
Example Output:
| customer_id | first_name | last_name | state | account_status | account_balance |
|---|---|---|---|---|---|
| 1050 | John | Doe | NY | active | 105500 |
| 3050 | Sam | Green | NY | active | 305000 |
SQL Question 7: What's the purpose of a primary key?
A primary key is a column or group of columns that uniquely identifies a row in a table. For example, say you had a database of Vanguard marketing campaigns data:
In this Vanguard example, the CampaignID column is the primary key of the MarketingCampaigns table. The constraint ensures that no two rows have the same CampaignID. This helps to maintain the integrity of the data in the table by preventing duplicate rows.
SQL Question 8: Calculate the Average Investment Balance Per Portfolio
A Portfolio Manager at Vanguard wants to review the average balance of each investment portfolio over the past quarter. Write a SQL query that calculates the average balance for each portfolio over this time period.
Example Input:
| portfolio_id | investor_id | portfolio_name |
|---|---|---|
| 1 | 200 | Tech Growth |
| 2 | 250 | Balanced Income |
| 3 | 300 | Aggressive Growth |
| 4 | 350 | Defensive Income |
| 5 | 400 | European Diversified |
Example Input:
| portfolio_id | date | balance |
|---|---|---|
| 1 | 2022-07-15 | 50000.00 |
| 1 | 2022-08-15 | 55000.00 |
| 2 | 2022-07-15 | 60000.00 |
| 2 | 2022-08-15 | 65000.00 |
| 3 | 2022-07-15 | 70000.00 |
| 3 | 2022-08-15 | 75000.00 |
| 4 | 2022-07-15 | 80000.00 |
| 4 | 2022-08-15 | 85000.00 |
| 5 | 2022-07-15 | 90000.00 |
| 5 | 2022-08-15 | 95000.00 |
Example Output:
| portfolio_name | average_balance |
|---|---|
| Tech Growth | 52500.00 |
| Balanced Income | 62500.00 |
| Aggressive Growth | 72500.00 |
| Defensive Income | 82500.00 |
| European Diversified | 92500.00 |
Answer:
This SQL query joins the and tables based on the column. It then limits the data to the specified quarter via a WHERE clause. It finally calculates the average balance per portfolio by using the AVG aggregate function, grouping the balances by the portfolio name.
To practice a very similar question try this interactive Amazon Average Review Ratings Question which is similar for averaging data or this Alibaba Compressed Mean Question which is similar for mean calculations.
SQL Question 9: Find Average Investment Per Client
Vanguard is a company offering mutual funds, ETFs, and retirement accounts. Consider the following scenario for Vanguard:
Vanguard wants to understand its customers' behavior when it comes to investing. They have two tables: and . The table keeps track of information about their clients, and each row represents one client. The table logs each transaction the client made, meaning each row is one investment made by a client.
Calculate the average investment amount per investor.
Example Input:
| investor_id | investor_name |
|---|---|
| 1 | John Doe |
| 2 | Jane Smith |
| 3 | Bob Johnson |
Example Input:
| investment_id | investor_id | investment_date | investment_amount |
|---|---|---|---|
| 101 | 1 | 01/04/2022 00:00:00 | 500 |
| 102 | 1 | 01/10/2022 00:00:00 | 200 |
| 103 | 2 | 01/12/2022 00:00:00 | 800 |
| 104 | 3 | 02/15/2022 00:00:00 | 300 |
| 105 | 3 | 03/05/2022 00:00:00 | 200 |
Example Output:
| investor_name | avg_investment |
|---|---|
| John Doe | 350 |
| Jane Smith | 800 |
| Bob Johnson | 250 |
Answer:
In this SQL query, we first join and on . Then, we group the results by to calculate the average investment amount () per investor.
SQL Question 10: Can you describe a cross-join and its purpose?
A cross-join, also known as a cartesian join, is like a mad scientist's laboratory experiment gone wild. It takes two tables and mixes them together to create a crazy new table with every possible combination of rows from the original tables.
Here's an example:
If you have 20 products and 10 colors, that's 200 rows right there! Cross-joins are great for generating all possible combinations, but they can also create really big tables if you're not careful. Just like a mad scientist, use your powers wisely!
SQL Question 11: Find all Vanguard customers whose email addresses end with 'gmail.com'
Assume that you are a data analyst at Vanguard and you are given a task to find all the customers who have signed up using a Gmail email address. Write a SQL query to find these customers. You will be directly querying the 'customers' table in the Vanguard database. Each record in the 'customers' table is a unique customer and has fields for 'customer_id', 'first_name', 'last_name', 'email' and 'sign_up_date'.
Table Example Input:
| customer_id | first_name | last_name | sign_up_date | |
|---|---|---|---|---|
| 1 | John | Doe | johndoe@gmail.com | 2019-01-01 |
| 2 | Jane | Doe | janedoe@yahoo.com | 2019-02-01 |
| 3 | Jim | Brown | jimbrown@gmail.com | 2020-03-03 |
| 4 | Julia | Richards | juliarichards@outlook.com | 2021-04-04 |
| 5 | Jack | Miller | jackmiller@gmail.com | 2021-05-05 |
Answer:
The above SQL query filters the 'customers' table to only show records where the 'email' column ends with 'gmail.com'. The '%' before 'gmail.com' in the LIKE clause is a wildcard that matches any sequence of characters. In the context of this problem, it matches any email address that ends with 'gmail.com'. This query should return the customers with customer_ids 1, 3, and 5.
Preparing For The Vanguard SQL Interview
Assuming that you've already got basic SQL skills, the next best tip we have to prepare for the Vanguard SQL interview is to solve as many practice SQL interview questions as you can!
Besides solving the earlier Vanguard SQL interview questions, you should also solve the 200+ DataLemur SQL Interview Questions which come from companies like FAANG (FB, Apple, Amazon, Netflix, Google).
Each interview question has hints to guide you, detailed solutions and best of all, there's an online SQL coding environment so you can easily right in the browser your SQL query and have it checked.
To prep for the Vanguard SQL interview you can also be useful to practice SQL questions from other investment management and private equity companies like:
But if your SQL skills are weak, forget about jumping right into solving questions – go learn SQL with this interactive SQL tutorial.
This tutorial covers topics including handling strings and filtering strings based on patterns – both of these show up routinely in Vanguard interviews.
Vanguard Data Science Interview Tips
What Do Vanguard Data Science Interviews Cover?
Besides SQL interview questions, the other question categories to prepare for the Vanguard Data Science Interview are:
- Statistics and AB Testing Questions
- Python or R Programming Questions
- Analytics and Product-Metrics Questions
- ML Interview Questions
- Behavioral Interview Questions
How To Prepare for Vanguard Data Science Interviews?
The best way to prepare for Vanguard Data Science interviews is by reading Ace the Data Science Interview. The book's got:
- 201 Interview Questions from FAANG & startups
- A Crash Course on SQL, AB Testing & ML
- Amazing Reviews (1000+ 5-star reviews on Amazon)