(Ex-Facebook & Best-Selling Data Science Author)
December 4, 2023
At Raytheon Technologies, SQL is often used for analyzing aerospace defense data for strategic insights and managing satellite-collected sensor data for efficient data retrieval and storage. Unsurprisingly this is why Raytheon LOVES to ask SQL problems during interviews for Data Analyst, Data Science, and BI jobs.
So, if you're preparing for a SQL Interview, we've curated 8 Raytheon Technologies SQL interview questions to practice, which are similar to recently asked questions at Raytheon – how many can you solve?
At Raytheon, one of the data analyst's responsibilities could be understanding and analyzing the sales and performance of the different missile systems produced by the company.
Given the following two tables:
Now, design a SQL query to find the cumulative monthly sales quantity for each product from the table, sorted by the product and the month.
Please consider the launch date in the table. Only include sales that occurred after the launch date of the product.
This query begins with a CTE (), which aggregates the total quantity of sales by product and month. We subsequently join this with the table using another CTE () while ensuring that we only include sales that occurred after the launch date of the product.
In the final query, we utilize a window function to calculate the cumulative quantity of product sales, partitioning by the and ordering by the . Ultimately, this gives us a table containing each product's cumulative monthly sales since its launch.
Pro Tip: Window functions are a popular SQL interview topic, so practice all the window function problems on DataLemur
Raytheon uses digital marketing to publicize its job opportunities. A central KPI they track is the click-through rate, which is the ratio of users who click on a specific link to the number of total users who view a webpage, ad or email. For this question, let's focus on the click-through rate from the job listing page to the application page.
You need to calculate the click-through rate. For each job title, calculate the ratio of users who viewed the job listing (page_view) and then subsequently clicked to the application page (clicked_apply).
Here's your data.
|Cyber Security Analyst
The SQL query to solve this problem would be as follows:
This query first joins the user interaction data with the job postings. It then groups the data by job title. It calculates the 'click through rate' by taking the sum of 'clicked_apply'(which is either 1 or 0) divided by the count of 'page_view'. Though 'page_view' is same for all the interactions but for theoretical purposes this gives the correct Click-Through-Rate.
To practice another question about calculating rates, solve this TikTok SQL Interview Question on DataLemur's online SQL coding environment:
The clause works similarly to the clause, but it is used to filter the groups of rows created by the clause rather than the rows of the table themselves.
For example, say you were analyzing Raytheon sales data:
This query retrieves the total sales for all products in each region, and uses the clause to only sales made after January 1, 2023. The rows are then grouped by region and the clause filters the groups to include only those with total sales greater than $500k.
The Defense Contractor Raytheon deals with multiple government projects all the time, for various state and federal clients. Write a SQL query that will report the average project completion time for each client.
This query first calculates the number of days for each project by taking the difference between and . This is done with the DATEDIFF function. It then groups the results by and calculates the average project completion time for each client by using the AVG function.
A correlated sub-query is one that is linked to the outer query and cannot be executed on its own. It uses the outer query to filter or transform data by referencing a column from the outer query, while the outer query uses the results of the inner query. On the other hand, 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 for the outer query.
Correlated sub-queries are 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.
Raytheon, a major U.S. defense contractor, maintains a variety of military equipment. Given a database that includes two tables - and , the company wants to have a report that shows all the equipment that were maintained in the last month and the average duration of maintenance.
The table contains information about each piece of equipment, including its , , and . It can be considered as follows:
|Fighter Jet F2
The table includes details of maintenance activities on the equipment, such as the , , , and .
To achieve this, we can join both tables and filter for records where the falls in the last month. We then group by and calculate the average duration of maintenance for each.
This query gives the average maintenance duration of military equipment that finished maintenance in the last month.
A primary key is a column (or set of columns) in a table that uniquely identifies each row in the table. It cannot contain null values and must be unique across all rows in the table.
A foreign key is a column (or set of columns) in a table that references the primary key of another table. It is used to establish a relationship between the two tables. A foreign key can contain null values, and multiple rows in the referencing table can reference the same row in the referenced table.
For example, consider a database with two tables: and . The Raytheon customers table might have a primary key column called , while the Raytheon orders table might have a foreign key column called that references the column in the table. This establishes a relationship between the two tables, such that each row in the orders table corresponds to a specific Raytheon customer.
The best way to prepare for a Raytheon SQL interview is to practice, practice, practice. Beyond just solving the earlier Raytheon SQL interview questions, you should also solve the 200+ SQL exercises on DataLemur which come from companies like FAANG (FB, Apple, Amazon, Netflix, Google).
Each problem on DataLemur has multiple hints, fully explained answers along with a discussion board to see how others solved it and best of all, there's an interactive SQL code editor so you can easily right in the browser your SQL query and have it graded.
To prep for the Raytheon SQL interview you can also be helpful to practice interview questions from other defense & aerospace contractors like:
However, if your SQL query skills are weak, don't worry about going right into solving questions – strengthen your SQL foundations with this free SQL tutorial.
For the Raytheon Data Science Interview, in addition to SQL query questions, the other types of questions which are covered:
The best way to prepare for Raytheon Data Science interviews is by reading Ace the Data Science Interview. The book's got: