10 T. Rowe Price SQL Interview Questions (Updated 2024)
T. Rowe Price employees use SQL for extracting and analyzing investment data, and managing the databases storing client financial profiles. That's the reason behind why T. Rowe Price asks SQL questions during interviews for Data Science, Data Engineering and Data Analytics jobs.
Thus, to help you prepare, we've collected 10 T. Rowe Price SQL interview questions – able to answer them all?
10 T. Rowe Price SQL Interview Questions
SQL Question 1: Identify VIP Customers at T. Rowe Price
Given the "trades" and "customers" tables below, identify T. Rowe Price's Top 5 VIP Customers in the last 6 months, based on the total investment amount, assume the current date is '2022-09-30'.
Example Input:
| trade_id | customer_id | trade_date | investment_amount |
|---|---|---|---|
| 10001 | 001 | 2022-04-10 | 500000 |
| 10002 | 001 | 2022-05-01 | 300000 |
| 10003 | 002 | 2022-07-15 | 250000 |
| 10004 | 002 | 2022-08-20 | 350000 |
| 10005 | 003 | 2022-03-12 | 700000 |
| 10006 | 003 | 2022-04-30 | 400000 |
Sample Data:
| customer_id | first_name | last_name | |
|---|---|---|---|
| 001 | John | Doe | johndoe@email.com |
| 002 | Jane | Doe | janedoe@email.com |
| 003 | Sam | Smith | samsmith@email.com |
Answer:
This query first joins the and tables on . It then filters for trades that were made in the last 6 months. It groups the result by , sums for each customer_id, and orders the result in descending order based on . Finally, it limits the output to the top 5, representing our VIP customers.
To practice another SQL customer analytics question where you can code right in the browser and have your SQL code automatically checked, try this Walmart Labs SQL Interview Question:
SQL Question 2: Department Salaries
You're given a table of T. Rowe Price employee and department salaries. Write a SQL query to find departments where the departments average salary is higher than the company's average salary.
Try this problem directly within the browser on DataLemur:
The answer is LONG – 30+ lines of SQL. You can find a step-by-step solution with hints here: Department vs. Company Salary.
Check out the T. Rowe Price career page and see what type of role is best suited for you!
SQL Question 3: How would you speed up a slow SQL query?
Here's some strategies that can generally speed up a slow SQL query:
- Only query the columns you actually need
- Index the columns used in the query
- Use the right kind of JOIN (be explicit about inner vs. outer joins)
- Use the right data types (for example INT vs BIGINT can save you disk space and memory)
While there's an entire industry dedicated to database performance tuning , for Data Analyst and Data Science interviews at T. Rowe Price, knowing the above basics should be more than enough to ace the SQL interview! Data Engineers on the other hand should know more about the command and understand a bit more about a query-execution plan.
SQL Question 4: Quarterly Investment Performance Ranking
Question Description: T. Rowe Price has thousands of investments across multiple portfolios. Given data on the performance of different investments for each quarter of the year, write a SQL query to find the rank of each investment by return percentage within each portfolio for each quarter using a window function.
Sample Data:
Example Input:
| investment_id | portfolio_id | quarter | year | return_percent |
|---|---|---|---|---|
| 1023 | 501 | 1 | 2020 | 3.5 |
| 2345 | 502 | 1 | 2020 | 4.2 |
| 1207 | 501 | 2 | 2020 | 2.1 |
| 2384 | 502 | 2 | 2020 | 5.5 |
| 2864 | 503 | 1 | 2020 | 2.8 |
| 1523 | 501 | 1 | 2021 | 4.1 |
| 3768 | 502 | 1 | 2021 | 3.5 |
Example Output:
| investment_id | portfolio_id | quarter | year | return_percent | ranking |
|---|---|---|---|---|---|
| 1023 | 501 | 1 | 2020 | 3.5 | 1 |
| 2345 | 502 | 1 | 2020 | 4.2 | 1 |
| 1207 | 501 | 2 | 2020 | 2.1 | 1 |
| 2384 | 502 | 2 | 2020 | 5.5 | 1 |
| 2864 | 503 | 1 | 2020 | 2.8 | 1 |
| 1523 | 501 | 1 | 2021 | 4.1 | 1 |
| 3768 | 502 | 1 | 2021 | 3.5 | 2 |
Answer:
This query uses the window function to rank the investments within each portfolio for each quarter and year based on their return performance. The PARTITION BY clause separates the data into windows defined by the portfolio_id, year, and quarter, and within each window, the investments are ordered by the return percent in descending order and assigned a rank. The ranks are then added as a new column in the output. If there's a tie in return percentage, the same rank is assigned and the next rank in the sequence is skipped.
For more window function practice, try this Uber SQL Interview Question within DataLemur's online SQL coding environment:
SQL Question 5: Could you describe a self-join and provide a scenario in which it would be used?
A self-join is a type of JOIN where a table is joined to itself. To execute a self-join, you must include the table name twice in the FROM clause and assign a different alias to each instance. You can then join the two copies of the table using a JOIN clause, and use a WHERE clause to specify the relationship between the rows.
For instance, suppose you had website visitor data for T. Rowe Price, exported from the company's Google Analytics account. To assist the web-dev team, you needed to analyze pairs of pages for UX or navigational issues. As part of that analysis, you wanted to generate all pairs of URLs, but needed to exclude pairs where both URLs were the same since that is not a valid pair."
You could use the following self-join:
This query returns the url of each page () along with the url of the page that referred to it (). The self-join is performed using the field, which specifies the id of the page that referred the visitor to the current page, and avoids any pages that referred themself (aka data anomalies).
SQL Question 6: Managing Customer Portfolio
T. Rowe Price, a global investment management firm, wants a system to manage their clients' investment profiles, keep track of different types of investments, and easily generate a report detailing the performance of each investment in a specified timeframe.
There are three tables in this setup: , , and .
table:
| client_id | name | |
|---|---|---|
| 101 | John Doe | john@gmail.com |
| 102 | Jane Smith | jane@gmail.com |
| 103 | David Johnson | david@gmail.com |
table:
| investment_id | client_id | investment_type |
|---|---|---|
| 201 | 101 | Stocks |
| 202 | 102 | Bonds |
| 203 | 103 | Mutual Funds |
| 204 | 101 | Real Estate |
| 205 | 102 | Stocks |
| 206 | 103 | Bonds |
table:
| investment_id | date | return_percentage |
|---|---|---|
| 201 | 2021-06-30 | 5 |
| 202 | 2021-06-30 | -1 |
| 203 | 2021-06-30 | 6 |
| 204 | 2021-06-30 | 7 |
| 205 | 2021-06-30 | 1 |
| 206 | 2021-06-30 | 3 |
SQL Interview question: Write a SQL query that retrieves a list of clients along with the total return they have earned for the month of June 2021 from their investments.
Answer:
This query joins the , , and tables to generate a report of returns earned by each client in the specified timeframe. It uses function to filter out the data for June 2021 and function to calculate the total returns.
SQL Question 7: Could you provide a list of the join types in SQL and explain what each one does?
A join in SQL combines rows from two or more tables based on a shared column or set of columns.
Four types of JOINs exist in SQL. To demonstrate each one, say you had a table of T. Rowe Price orders and T. Rowe Price customers.
INNER JOIN: When there is a match in the shared key or keys, rows from both tables are retrieved. In this example, an between the Orders and Customers tables would retrieve rows where the in the Orders table matches the in the Customers table.
LEFT JOIN: A retrieves all rows from the left table (in this case, the Orders table) and any matching rows from the right table (the Customers table). If there is no match in the right table, NULL values will be returned for the right table's columns.
RIGHT JOIN: A retrieves all rows from the right table (in this case, the Customers table) and any matching rows from the left table (the Orders table). If there is no match in the left table, NULL values will be returned for the left table's columns.
FULL OUTER JOIN: A retrieves all rows from both tables, regardless of whether there is a match in the shared key or keys. If there is no match, NULL values will be returned for the columns of the non-matching table.
SQL Question 8: Calculate the Average Investment Fund Return
T. Rowe Price is a well known investment management firm. Consider you are given a table named 'InvestmentFunds' where each row represents a different investment fund managed by the company. Each fund has a 'fund_id', 'fund_name', and 'return_percentage' for every year. Now, your task is to find the average return of each fund over the years.
Given the following table named .
Example Input:
| fund_id | fund_name | year | return_percentage |
|---|---|---|---|
| 1 | Global Technology Fund | 2018 | 15.6 |
| 1 | Global Technology Fund | 2019 | 18.2 |
| 1 | Global Technology Fund | 2020 | 21.1 |
| 2 | Equity Income Fund | 2018 | 9.4 |
| 2 | Equity Income Fund | 2019 | 7.8 |
| 2 | Equity Income Fund | 2020 | 8.6 |
We would like to calculate the average return for each fund.
Answer:
The above query groups the InvestmentFunds table by fund_id and fund_name, then it calculates the average of the return percentage for each fund.
Example Output:
| fund_id | fund_name | avg_return_percentage |
|---|---|---|
| 1 | Global Technology Fund | 18.3 |
| 2 | Equity Income Fund | 8.6 |
As a result, we get the average return for each fund over the years.
To practice a very similar question try this interactive Amazon Average Review Ratings Question which is similar for need to aggregate periodic data or this Alibaba Compressed Mean Question which is similar for <need to calculate average of data.
SQL Question 9: Analyzing Click-through-rates for T. Rowe Price
Suppose T. Rowe Price would like to analyse the click-through rates of their digital ads for their various investment products. They are especially interested in understanding which products have the highest click-to-add-to-cart conversion rates.
Given two tables, and , calculate the click-to-add-to-cart conversion rate for each product. The conversion rate is defined as the number of times a product is added to cart divided by the total number of clicks on the digital ads for that product.
Example Input:
| ad_id | click_date | user_id | product_id |
|---|---|---|---|
| 7123 | 05/07/2022 00:00:00 | 318 | 40003 |
| 8592 | 06/15/2022 00:00:00 | 421 | 40003 |
| 9283 | 04/22/2022 00:00:00 | 562 | 50010 |
| 2305 | 07/11/2022 00:00:00 | 872 | 50010 |
| 7382 | 08/13/2022 00:00:00 | 212 | 60020 |
Example Input:
| add_to_cart_id | add_date | user_id | product_id |
|---|---|---|---|
| 9801 | 05/07/2022 00:00:00 | 318 | 40003 |
| 3265 | 06/22/2022 00:00:00 | 421 | 40003 |
| 8723 | 04/30/2022 00:00:00 | 562 | 50010 |
| 5392 | 07/14/2022 00:00:00 | 872 | 50010 |
| 5941 | 08/15/2022 00:00:00 | 212 | 60020 |
Answer:
This query joins the and tables on and . It also ensures that a click occurs before or at the same time an item is added to cart. Following this, it calculates the click-to-add-to-cart conversion rate as the ratio of the count of distinct s in the table to the count of distinct s in the table.
To solve a related SQL interview question on DataLemur's free online SQL coding environment, solve this Meta SQL interview question:
SQL Question 10: What do the SQL commands / do?
The / operator is used to remove to return all rows from the first SELECT statement that are not returned by the second SELECT statement.
Note that is available in PostgreSQL and SQL Server, while MINUS is available in MySQL and Oracle (but don't stress about knowing which DBMS supports what exact commands since the interviewers at T. Rowe Price should be lenient!).
For a tangible example in PostgreSQL, suppose you were doing an HR Analytics project for T. Rowe Price, and had access to T. Rowe Price's contractors and employees data. Assume that some employees were previously contractors, and vice versa, and thus would show up in both tables. You could use operator to find all contractors who never were a employee using this query:
T. Rowe Price SQL Interview Tips
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 T. Rowe Price SQL interview questions, you should also solve the 200+ DataLemur interview questions which come from companies like Google, Facebook, Microsoft and Amazon.
Each problem on DataLemur has multiple hints, fully explained answers along with a discussion board to see how others solved it and crucially, there's an interactive SQL code editor so you can right online code up your query and have it checked.
To prep for the T. Rowe Price SQL interview it is also wise to practice interview questions from other investment management and private equity companies like:
In case your SQL foundations are weak, forget about going right into solving questions – refresh your SQL knowledge with this free SQL for Data Analytics course.
This tutorial covers things like using ORDER BY and filtering groups with HAVING – both of these come up frequently during SQL interviews at T. Rowe Price.
T. Rowe Price Data Science Interview Tips
What Do T. Rowe Price Data Science Interviews Cover?
Besides SQL interview questions, the other types of questions tested in the T. Rowe Price Data Science Interview are:
- Experimental Design & AB Testing Questions
- Python Pandas or R Coding Questions
- Product & Business Analytics Questions
- ML Modelling Questions
- Behavioral Based Interview Questions
How To Prepare for T. Rowe Price Data Science Interviews?
I'm a bit biased, but I believe the optimal way to prepare for T. Rowe Price Data Science interviews is to read the book Ace the Data Science Interview.
The book covers 201 data interview questions taken from FAANG (FB, Apple, Amazon, Netflix, Google). It also has a crash course on Stats, SQL & ML. And finally it's vouched for by the data community, which is how it's gotten to be an Amazon best-seller with over 1000+ 5-star reviews.