Zoox Inc. Data Engineer Interview Questions + Guide in 2024

Zoox Inc. is trailblazing the future of autonomous mobility by developing the first ground-up, fully autonomous vehicle fleet. Merging artificial intelligence, robotics, and design, Zoox aims to revolutionize urban transportation by offering a unique mobility-as-a-service experience.

As a Data Engineer at Zoox, you will play a crucial role in developing and maintaining robust data pipelines that leverage data from our autonomous vehicles. This data is essential for making strategic decisions and ensuring the readiness of our services. You will work with cutting-edge technologies such as Airflow, Kafka, Spark, and Hadoop to build a scalable data infrastructure that supports analytics and enables data-driven decision-making.

This guide will give you detailed insights into what Zoox is looking for in candidates and some sample Zoox data engineer interview questions you need to prepare for.

Typically, interviews at Zoox Inc. vary by role and team, but commonly Data Engineer interviews follow a fairly standardized process across these question topics.

Submitting Your Application

The first step is to submit a compelling application that reflects your technical skills and interest in joining Zoox Inc. as a data team member. Whether you were contacted by a Zoox recruiter or have taken the initiative yourself, carefully review the job description and tailor your CV according to the prerequisites.

Tailoring your CV may include identifying specific keywords that the hiring manager might use to filter resumes and crafting a targeted cover letter. Furthermore, don’t forget to highlight relevant skills and mention your work experiences, especially those related to autonomous vehicles and large-scale data systems.

Recruiter/Hiring Manager Call Screening

If your CV happens to be among the shortlisted few, a recruiter from the Zoox Talent Acquisition Team will make contact and verify key details like your experiences and skill level. Behavioral questions may also be a part of the screening process.

In some cases, the Zoox hiring manager stays present during the screening round to answer your queries about the role and the company itself. They may also indulge in surface-level technical and behavioral discussions.

The whole recruiter call should take about 30 minutes.

CoderPad Technical Interview

Successfully navigating the recruiter round will present you with an invitation for the technical screening round. Technical screening for Zoox roles usually is conducted through virtual means, such as a CoderPad interview. The hiring manager may ask you to solve coding problems live, which could involve developing and troubleshooting data pipelines, optimizing code for performance, and demonstrating advanced proficiency in languages like C++, Python, or Scala.

This stage can last around 1 hour and covers both your problem-solving skills and your ability to write clean, efficient code.

Onsite Interview Rounds

Followed by a second recruiter call outlining the next stage, you’ll be invited to attend the onsite interview loop. Multiple interview rounds, varying with the role, will be conducted during your day at the Zoox office. Your technical prowess, including programming capabilities in C++/Python/Scala and building data infrastructure at scale, will be evaluated against the finalized candidates throughout these interviews.

If you were assigned take-home exercises, a presentation round may also await you during the onsite interview for the data team role at Zoox.

Quick Tips For Zoox Data Team Interviews

• Understand Autonomous Vehicles: Zoox’s work revolves around autonomous vehicle data. Familiarize yourself with the basics and recent advancements in this domain to show that you understand the broader impact of the work.
• Highlight Data Pipeline Experience: Demonstrate your experience with data pipelines, large-scale data processing frameworks (e.g., Spark, Hadoop), and workflow managers (e.g., Airflow). Practical knowledge in these areas will be highly beneficial.
• Be Versatile with Languages: Zoox values proficiency in multiple programming languages, particularly Python, C++, Scala, and tools for data streaming (e.g., Kafka). Showcasing versatility with these languages will make you a strong candidate.

By following these steps and tips, you’ll be well-prepared to navigate the Zoox interview process with confidence. Best of luck!

Practice for the interview with these recently asked Zoox Inc. data engineer interview questions:

1. Write a function digit_accumulator to sum every digit in a floating-point number string

You are given a string that represents some floating-point number. Write a function, digit_accumulator, that returns the sum of every digit in the string.

Example:

Input:

s = "123.0045"

Output:

def digit_accumulator(s) -> 15

Since 
1 + 2 + 3 + 0 + 0 + 4 + 5 = 15

2. Describe strategies to reduce tech debt and improve developer turnaround time.

Suppose that you work at a fintech startup. Recently, management has raised the issue of the increased amount of developer hours needed to implement relatively simple features, citing tech debt as the primary cause. How would you go around decreasing tech debt and decreasing developer turnaround time?

3. Create a function to find the nearest common ancestor of two nodes in a binary tree.

You are given a binary tree of unique positive numbers. Each node in the tree is implemented as a dictionary with the keys left and right, indicating the node’s left and right neighbors, respectively, and data that holds an integer value. Given two nodes as input (value1 and value2), write a function to return the value of the nearest node that is a parent to both nodes. If one of the nodes doesn’t exist in the tree, return -1.

Example:

Input:

# Diagram of the binary tree
'''
      6        
     / \        
    3   9     
   / \
  2   11
     / \
    5   8
'''
value1 = 8
value2 = 2

Output:

common_ancestor(root,value1,value2) -> 3

As the parents for the nodes 8 and 2 are the root node 6 and the node 3, 3 is the nearest parent that has the two nodes as children.

4. Develop a function to determine the robot’s path in a 4x4 matrix.

A robot has been designed to navigate a two-dimensional 4x4 matrix by only moving forward or turning right when blocked by a wall of the matrix. Its starting position is in the top left corner of the matrix, denoted by (0,0), and the robot’s final destination is the bottom right corner. Determine the full path of the robot before it hits the final destination or starts repeating the path.

The ‘walls’ of the matrix are either one of the four borders of the map or any block found within.

A ‘Block’ is donated by having 1 in the cell corresponding to it where an empty cell is having ‘0’.

Example 1:

Input

robot_map = [
  [0,0,0,0],[0,0,1,0],[0,1,0,0],[0,0,0,0]
]

Output

robot_path(robot_map) -> [(0,0),(0,1),(0,2),(0,3),(1,3),(2,3),(3,3)]

As seen in these diagrams, the robot’s path starts with this sequence of steps:

1. Goes forward three times and hits the wall. Turns right.
2. Goes forward three times (orientation has changed), 3. Reaches the final destination and stops.

Example 2:

Input

robot_map = [
  [0,0,1,0],[0,0,0,0],[0,1,0,0],[0,0,0,0]
]

Output

robot_path(robot_map) -> [(0,0),(0,1),(1,1),(1,0)]

Here, the robot moves forward one space, but hits the wall. After turning right, another wall is hit, starting a loop.

To practice Algorithms interview questions, consider using the Python learning path or the full list of Algorithms questions in our database.

5. How would you improve Google Maps?

As the PM on Google Maps, what specific features or enhancements would you implement to improve the user experience?

6. What metrics would you check to see if your feature improvements are successful?

Identify the key performance indicators (KPIs) you would monitor to evaluate the success of your feature improvements on Google Maps.

7. What factors could have biased Jetco’s boarding time study results?

Jetco’s study showed the fastest average boarding times. What potential biases or factors could have influenced these results, and what would you investigate further?

8. How would you decrease tech debt and developer turnaround time at a fintech startup?

Management has raised concerns about increased developer hours due to tech debt. What strategies would you implement to reduce tech debt and improve developer turnaround time?

9. How would you design an incentive scheme for Uber drivers to go into high-demand city areas?

Design an incentive scheme that encourages Uber drivers to operate in city areas where demand is high.

10. Customer success manager vs. free trial for Square’s new software product?

The CEO wants to hire a customer success manager, while another executive suggests a free trial. What would be your recommendation for getting new or existing customers to use Square’s new software product?

To prepare for analytics and experiments, consider using the product metrics learning path and the data analytics learning path.

11. How would you evaluate a method or algorithm to match users with their siblings on Facebook?

A product manager has asked you to develop a method to match users to their siblings on Facebook. How would you evaluate the effectiveness of this method or algorithm, and what metrics might you use?

12. How would you decrease tech debt and developer turnaround time at a fintech startup?

Management has raised concerns about the increased developer hours needed to implement simple features, citing tech debt as the primary cause. How would you address tech debt and improve developer turnaround time?

To get ready for machine learning interview questions, we recommend taking the machine learning course.

13. What metrics and statistical methods would you use to identify dishonest users in a sports app?

You work for a company with a sports app that tracks running, jogging, and cycling data. To identify users who might be cheating (e.g., driving a car while claiming to bike), what metrics would you analyze and what statistical methods would you use to detect athletic anomalies?

To prepare for statistics and probability interview questions, consider using the comprehensive probability learning path. These resources cover essential concepts, including A/B testing, multivariate distributions, and sampling theorems.

To prepare for a Zoox Data Engineer interview, focus on these key areas:

• Learn Data Engineering Fundamentals: Brush up on SQL, ETL processes, and data modeling. Practice writing complex queries and designing pipelines and familiarize yourself with Spark, Kafka, and distributed systems. Understand how to process large-scale data in real-time.

• Brush Up Programming Skills: Strengthen your Python (or Scala) skills and practice solving coding challenges, focusing on data structures and algorithms.

• Practice on Behavioral Interview: Practice behavioral interview questionsto show how you work and your fit in the company.

• Do Mock Interviews: Getting real-time feedback is one of the best ways to prepare for an interview. Consider doing a peer-to-peer mock interview or trying out our AI interviewer to learn your areas of improvement quickly.

What is the average salary for a Data Engineer at Zoox?

Are there any openings at Zoox Inc?

Check out our Job Board to check any current openings at Zoox Inc.

Getting ready for a data engineer interview at Zoox can be challenging, but we believe this guide will equip you to land the role.

If you want to learn more about Zoox, consider checking out our main Zoox interview guide for more information.

We wish you the best!