10 Aurora Innovation SQL Interview Questions (Updated 2024)

At Aurora Innovation, SQL is used all the damn time for analyzing vast amounts of autonomous vehicle data for insights. For this reason Aurora Innovation often tests SQL coding questions in interviews for Data Science, Analytics, and & Data Engineering jobs.

To help you prepare for the Aurora Innovation SQL interview, this blog covers 10 Aurora Innovation SQL interview questions – able to answer them all?

10 Aurora Innovation SQL Interview Questions

SQL Question 1: Identify VIP Users for Aurora Innovation

Aurora Innovation is a company that focuses on the development of autonomous vehicle technology. The "rides" table logs each ride a user takes, while the "users" table contains profile information for each user. A VIP user in the context of Aurora Innovation is defined as a user who has taken more than 40 rides in the past month.

Your task is to write SQL query that would help to identify these VIP users.

For this question, consider the following tables:

Example Input:

Example Input:

Answer:

This query counts all rides for each user in the past month using the 'rides' table. This information is then joined with the 'users' table to get the first and last name of the users. This intermediate result is filtered to only include users that have more than 40 rides in the past month.

To practice a similar power-user data analysis problem question on DataLemur's free interactive SQL code editor, try this Microsoft Teams Power User SQL Interview Question:

SQL Question 2: Analyze User Activity

As a company, Aurora Innovation develops self-driving technology. Suppose you are given access to the 'user_activity' table which logs the daily activity of users who are testing Aurora's automated vehicles.

The table has the following attributes:

Design a SQL query that will output a list of users who have increased their weekly miles driven by at least 200% over the previous week. It should contain following columns:

Example Input:

Example Output (considering Sunday as the start of the week, and at least 2 weeks of data available for the user):

Answer:

With PostgreSQL, you can use "date_trunc" function to aggregate by weeks, and "lag()" window function to calculate the previous week's miles.

This query first calculates the total miles driven per week per user. Then, it generates a lag column to store the miles driven in the previous week. It then calculates the percent change between these two weeks. Finally, it selects the rows where this percent change is greater or equal than 200.

Pro Tip: Window functions are a popular SQL interview topic, so practice all the window function problems on DataLemur

SQL Question 3: Could you clarify the difference between a left and a right join?

"In SQL, a join generally retrieves rows from multiple tables and combines them into a single result set. For an example of the difference between a left vs. right join, suppose you had a table of Aurora Innovation orders and Aurora Innovation customers.

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.

A combines 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 displayed for the left table's columns.

SQL Question 4: Analyzing Autonomous Vehicle Performance

Aurora Innovation is a company that designs and builds self-driving vehicles. Each vehicle has multiple sensors collecting data related to the vehicle's performance and environment.

Consider two tables:

• : This table stores information about each vehicle.

• : This table stores data related to each trip that a vehicle takes, including sensor data that rate the trip's performance (on a scale from 1-10), the date of the trip and the id of the vehicle that took the trip.

Your task is to generate a report that includes the average performance for each vehicle for a given month.

Example Input:

Example Input:

Answer:

The requested average performance per vehicle per month can be calculated using an SQL query that extracts the month from the trip date, groups the data by vehicle and month, and calculates the average performance for each group. A possible answer could look like this:

This query first JOINs the and tables on the column. The function is used to get the month part of the . The clause then separates the combined table into groups of rows that have the same , , and . The function calculates the average for each of these groups. The clause sorts the result first by , then , and finally .

SQL Question 5: What is the purpose of the SQL constraint ?

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A UNIQUE constraint ensures that all values in a column are different. This provides uniqueness for the column(s) and helps identify each row uniquely. Unlike primary key, there can be multiple unique constraints defined per table.

SQL Question 6: Filter Customer Records based on Multiple Boolean Conditions

At Aurora Innovation, we have a database of our autonomous vehicle test results with columns for Test ID, Vehicle ID, Test Date, Distance Traveled, and whether the test was Successful or not (True/False). We want to identify all tests conducted in 2022 that traveled over 1000 miles and were successful.

Please write a SQL query to help us filter down the test records database based on the stated conditions.

Example Input:

Example Output:

Answer:

The above SQL query will fetch the data from the table where the is in the year 2022, the is more than 1000, and the test was . The function is used to get only the year part of the . The result will be a table similar to the example output table with tests meeting these specific conditions.

SQL Question 7: What is the process for finding records in one table that do not exist in another?

To discover records in one table that are not present in another, you can utilize a and filter out any values in the right-side table.

For example, say you had a table of Aurora Innovation customers and a 2nd table of all purchases made with Aurora Innovation. To find all customers who did not make a purchase, you'd use the following

This query returns all rows from the customers table, along with any matching rows from the purchases table. If there is no matching row in the purchases table, values will be returned for all of the right table's columns. The clause then filters out any rows where the purchases.id column is , leaving only customers who have not made a purchase.

SQL Question 8: Average Distance Covered By Autonomous Vehicles

At Aurora Innovation, the company aims to deliver the benefits of self-driving technology safely, quickly, and broadly. Autonomous vehicles run different routes and cover different distances in a day. You are asked to write a SQL query that finds the average distance in miles covered by all the different vehicles per day.

Consider a table that shows the vehicle_id, the date of operation, and the distance it traveled on that day.

Example Input:

Your output should be a new table showing each date and the corresponding average distance covered by all vehicles.

Example Output:

Answer:

This SQL query calculates the average distance covered by the autonomous vehicles for each operation date. The clause groups the results by operation date and the function is applied to calculate the average distance for each group or each operation date. The clause ensures that the results are ordered by date.

To practice a very similar question try this interactive Amazon Server Utilization Time Question which is similar for requiring calculations over daily usage or this Tesla Unfinished Parts Question which is similar for working with daily operational data.

SQL Question 9: Calculate the Click-Through-Rate on Aurora Innovation's Marketing Campaigns

Aurora Innovation's marketing team is interested in understanding the effectiveness of their advertisements. To this end, you are asked to calculate the click-through rate (CTR) for each ad campaign they ran in the past month. The click-through rate is defined as the total number of clicks a campaign receives divided by the total number of impressions (views) that campaign gets. Each row in the table represents a unique click, and each row in the table represents a unique impression. You can assume that every click is preceded by an impression.

Example Input:

Example Input:

Example Output:

Answer:

In the query above, we're joining the and tables on the column. This allows us to count the number of clicks and impressions for each campaign. We then divide the number of clicks by the number of impressions to calculate the click-through rate(CTR) for each campaign.

To solve a related SQL problem on DataLemur's free online SQL code editor, try this Meta SQL interview question:

SQL Question 10: Could you describe the function of UNION in SQL?

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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 Aurora Innovation'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.

Aurora Innovation SQL Interview Tips

The best way to prepare for a Aurora Innovation SQL interview is to practice, practice, practice. Besides solving the above Aurora Innovation SQL interview questions, you should also solve the 200+ SQL questions from real Data Science & Analytics interviews which come from companies like Google, Microsoft and Silicon Valley startups.

Each interview question has multiple hints, detailed solutions and best of all, there's an interactive coding environment so you can instantly run your query and have it checked.

To prep for the Aurora Innovation SQL interview it is also helpful to solve SQL questions from other tech companies like:

• Tesla SQL questions

• Waymo SQL questions

• GM SQL questions

• Apple SQL questions

But if your SQL foundations are weak, forget about diving straight into solving questions – go learn SQL with this SQL tutorial for Data Analytics.

This tutorial covers things like CASE/WHEN/ELSE statements and LEFT vs. RIGHT JOIN – both of which show up routinely during Aurora Innovation SQL interviews.

Aurora Innovation Data Science Interview Tips

What Do Aurora Innovation Data Science Interviews Cover?

In addition to SQL interview questions, the other question categories to prepare for the Aurora Innovation Data Science Interview are:

• Probability & Stats Questions
• Coding Questions in Python or R
• Product Analytics Questions
• Machine Learning and Predictive Modeling Questions
• Resume-Based Behavioral Questions

How To Prepare for Aurora Innovation Data Science Interviews?

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

• 201 Interview Questions from Facebook, Google & startups
• A Refresher on SQL, AB Testing & ML
• Great Reviews (900+ reviews, 4.5-star rating)