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60+ Uber Data Engineer Interview Questions

by Interview Kickstart Team in Interview Questions
October 21, 2022

60+ Uber Data Engineer Interview Questions

Attend our Free Webinar on How to Nail Your Next Technical Interview


How To Nail Your Next Tech Interview

Hosted By
Ryan Valles
Founder, Interview Kickstart
Our tried & tested strategy for cracking interviews
How FAANG hiring process works
The 4 areas you must prepare for
How you can accelerate your learnings
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Uber Technologies is the world’s largest ridesharing company. A pioneer in the business, Uber brought about radical changes in the transportation industry. And it goes without saying that data is Uber’s most valuable asset, playing a critical role in Uber’s business since its inception in 2009. Therefore, the role of a data engineer at Uber is considered extremely lucrative. 

In this guide, we’ll delve into the company’s interview process for the role of a data engineer. Then, we’ll cover a set of Uber data engineer interview questions that you can use to practice for the interview so that you can be a step ahead of the competition.

Here’s what we’ll cover:

  1. Roles and Responsibilities of a Data Engineer at Uber
  2. Required Skills to Be a Data Engineer at Uber
  3. Types of Data Engineer Teams at Uber
  4. Uber Interview Process for Data Engineers
  5. Uber Interview Questions for Data Engineers
  6. Tips to Prepare for Your Uber Data Engineer Interview
  7. FAQs on Uber Data Engineer Role

Roles and Responsibilities of a Data Engineer at Uber

The exact work you do at Uber as a data engineer may vary depending on the team you join. Following are some examples of responsibilities assigned to data engineers at Uber:

  • Architect the company’s canonical data, which is central to all its decision-making processes across various operations and systems.
  • Build real-time streaming services and batch data pipelines to track and attribute user actions, such as taking rides, placing an order with Eats, etc.
  • Analyze and optimize data pipelines and workflows.
  • Develop a system that helps Uber target prospective users. This involves working with datasets on a world population scale, i.e., billions of rows.
  • Build systems that offer Uber access to free traffic.
  • Create a system that offers insights on inherent patterns underneath large volumes of data.

Required Skills to Be a Data Engineer at Uber

Being a tech company at its heart, Uber sets the bar very high for engineers. Following are all the requisites to join Uber as a data engineer:

Technical Skills

Alongside a solid foundation in software engineering, you must also be well-versed with the following:

  • Database systems (NoSQL and SQL).
  • Hadoop tech stack – Oozie, Hive, Spark, Airflow, MapReduce, etc.
  • Programming languages, such as Java, Python, and Scala, etc.
  • Large-scale data modeling and data warehousing architecture. 
  • Ability to build end-to-end and high-quality data solutions in an Agile environment.
  • Building pipelines of ETL data. 
  • Performance tuning and troubleshooting.

Soft Skills

In addition to technical skills, you should also have these soft skills in your arsenal:

  • Strong communication skills.
  • An ability to lead a team.
  • Presentation skills.
  • Collaboration skills.
  • Creativity and innovation.

Types of Data Engineer Teams at Uber

Uber has a dedicated data science and analytics team that transforms data about these areas of its business:

  • Safety and insurance
  • Uber Eats
  • Policy Rides
  • Risk
  • Platform
  • Marketing

Uber Interview Process for Data Engineer

Uber’s interview is a 4-step process, which comprises the following:

  1. Initial screening: A phone interview with the company’s hiring manager.
  2. Technical interview: Another phone interview that assesses your familiarity with ML algorithms as well as critical thinking.
  3. Take-home task: A hands-on assignment, which is due for submission after one week.
  4. On-site interview: 5-6 rounds of interviews that test your technical knowledge and cultural/behavioral fit. 

Read the Uber Tech Interview Process article for more information.

Uber Interview Questions for a Data Engineer 

The company assesses your merit through a number of problems related to Python and SQL. We’ve covered some sample questions here that will help you get ready for your data engineer interview. For some of the questions, we’ve also included pointers on how to solve the problem, which help you in your interview prep. 

Uber Data Engineer Python Interview Questions 

1. Find all unique combinations that are equal to the value of N in this given list of integers:
Integers = [2,3,5]
Target = 8
Output = [3, 5]

How to solve this problem: 

You will notice that this question breaks down into some identical subproblems. For instance, when the given integers are [2,3,5], and the target is 8, you can first solve for the input numbers, i.e., for integers [2,3,5], and the target is 8 - 2 = 6. So, you can just add 2 to the output and obtain the final answer. 

Essentially, this problem calls for you to use recursion.

2. Given a dictionary of roots and a sentence string. In the given sentence, stem words with the root forming it. Additionally, if any word has multiple roots, replace it with the roots of the shortest length.

Sentence: that cattle is rattled by the battery
roots = [“cat,” “bat,” “rat”]
Output: "that cat is rattled by the bat"

How to solve this problem: 

First, loop through each of the words in the sentence and check if the root exists in the word. If yes, simply replace a word with its root. If there is more than one root for the same word, replace the word with the root of the shortest length. However, as you are technically stemming these words, ensure that a root does not simply exist anywhere with its word and is equivalent to the word at its prefix.

After that, you can make this list of roots into a set, thus creating a root set. 

Here are the roots for the above sentence: [“cat,” “bat,” “rat”]

So, the output will be "that cat is rattled by the bat."

3. Let’s assume that you are given a log file of 100GB. Your task is to count the number of lines in this file using Python.

How to solve this problem: 

Before you dive straight into writing the code, take a while and think in terms of “efficiency.” For further clarity, ask yourself these questions:

  • How big is this file?
  • Will it be efficient to load this entire file?
  • Is it efficient to sift through this file line by line?

4. Given below is a string of integers representing page numbers. Write a function that returns this string’s last page number. Moreover, if this string is in incorrect page order, return its last number in order.
input = 12345678910111213; output = 13
input = 12345678; output = 8
input = 12345; output = 5

How to solve this problem:

A straightforward way to solve this problem is to iteratively loop through each value. Then, access each page number as it comes. Furthermore, you can dynamically eliminate values from the integer string. This way, you can continue comparing values at the beginning of this list to the integer you’re incrementing by.

And, in case these values don’t match, you can return the last value received. 

5. Without using built-in functions of NumPy, write a function that takes a list of integers and a list of dictionaries and returns the dictionary with a standard deviation for each of its lists.

How to solve this problem: 

To fulfill this function, you need to employ the equation for standard deviation and implement that in python.

Now that you have a fundamental idea of how to approach these questions, try solving the following problems:

  1. Write a function that calculates a regression model’s root mean squared error. This function should have two lists, one representing predictions and the other indicating target values.
  2. Given below is a list of test scores. Write code in Pandas and return the cumulative percentage of students with scores within the buckets of <100, <90, <75, and <50.
    User ID: 1, 2, 3, 4, 5
    Grade: 11, 10, 10,10, 11
    Test score: 99, 85, 60, 30, 90
  3. You’re given a text document with four phrases: I saw a dog; I saw a horse; I saw a dog; I have a cat. Determine the term frequency-inverse document frequency or TF-IDF for each term of the above document by writing a program in Python.
  4. Write a function that generates N samples from a random distribution of size M. Then, identify the lowest 5th and 6th values and return the average difference between them. Note: M must be greater than 6. Additionally, how will you verify if your function is returning the correct results?
  5. Let's say that a company's new users have been growing consistently from March to May in a particular city. However, its weekly metrics indicate a slow yet steady decline in the average number of comments per user from March to May in this city. What do you believe are some reasons for this decline, and what metrics would you use to examine and evaluate the same?

Uber Data Engineer SQL Interview Questions

1. Analyze the given data on employees and departments of a company:
a) Employees:
Columns: id, first_name, last_name, salary, department_id
Types: int, varchar, varchar, int, int
b) Departments:
Columns: id, name
Types: int, varchar
From the above data, pick out the top 3 departments with a minimum of 10 employees and rank them as per the percentage of employees earning a salary of over $100,000. 

How to solve this problem: 

First, take a moment to decode this problem. This will help you break it down so that you can subset it into distinct clauses of conditions:

  • Top 3 departments of the company
  • Percentage of employees earning more than $100,000 in salary
  • Departments must have a minimum of 10 employees

After that, you can use the query according to the clauses of conditions. 

2. You’re given a dataset of a company’s employees and departments:
a) Employees
id – int
first_name – varchar
last_name – varchar
salary – int
department_id – int
b) Department
id – int
name – varchar
Using this information, write an SQL query that selects the engineering department’s second-highest salary. Furthermore, your query should select the subsequent highest salary if more than one individual earns the highest salary. 

How to solve this problem: 

First, you need to associate each employee with the name of the department. Here, the field “department_id” is associated with the “id” field under the department section. As “department_id” is a column referencing another section’s primary key, it is a foreign key.

Based on this common field, you can join both of the tables by using INNER JOIN in SQL.

3. What are joins in SQL?

How to answer this question: 

We use a join clause to combine rows of two tables based on a related column between the tables. This clause, therefore, merges two tables and retrieves data. Joins are of 4 types, namely:

  • Full outer join
  • Inner join
  • Left join
  • Right join

4. How can you resolve an SQL query’s duplicate data points?

How to answer this question: 

You can suggest using “UNIQUE” and “DISTINCT” to eliminate duplicate data points. Further, you can highlight other ways to resolve duplicate data points, like using “GROUP BY” to group the data and filter it further.

Following are a few more Uber data engineer interview questions on SQL for practice:

  1. What are Entities and Relationships?
  2. Given below is a dataset on bank transactions:
    a) Column: user_id, created_at, transaction_value
    b) Type: int, DateTime, float
    Write a query to derive the total rolling 3-day average for deposits by day.
  3. From the data below, write a query to assess each day’s post success rate for July 2021.
    a) Column: id, user_id, created_at, action, url, platform
    b) Type: integer, integer, datetime, string, string, string
    Note: The “action” column indicates “post_enter,” “post_canceled,” or “post_submit.”
  4. What are the differences between MySQL and SQL?
  5. How can you migrate a 1GB dataset from a NoSQL database to a database based on SQL?

Uber Data Engineer Interview Questions (Other Topics)

In addition to Python and SQL problems, you can also expect questions on data engineering basics, Hadoop, and Hive. We’ve compiled an all-encompassing list of data engineer interview questions at Uber. Take a look: 

  1. Explain data engineering.
  2. What do you mean by data modeling?
  3. What is Hadoop streaming?
  4. What are the components of a Hadoop application? Explain each of them.
  5. How can you see MySQL’s database structure?
  6. Why do we use Hadoop’s commodity hardware?
  7. What data does NameNode store?
  8. Can you define Block Scanner and Block in HDFS?
  9. What do you mean by NameNode?
  10. What are the different types of design schemas in data modeling?
  11. Elaborate on the features of Hadoop.
  12. How can you deploy a big data solution?
  13. Which are the main methods of Reducer?
  14. What is Star Schema?
  15. What is Snowflake Schema?
  16. How can you achieve security in Hadoop?
  17. In Hadoop, what is a Heartbeat?
  18. What do you mean by FIFO scheduling?
  19. What is HDFS?
  20. Can you differentiate between unstructured and structured data?
  21. What is FSCK?
  22. Name the vs. of big data.
  23. Let’s say a Block Scanner detects corrupted data. What are the steps involved in this process?
  24. Why do software engineers use Hive in Hadoop’s eco-system?
  25. Explain the functionality of Secondary NameNode.
  26. Why does Hadoop use Context objects?
  27. What is the role of Metastore in Hive?
  28. What is SerDe in Hive? Explain various SerDe implementations.
  29. How does big data and data analytics increase a company’s revenue?
  30. Which two messages does a NameNode get from DataNode?
  31. Name Hadoop’s XML configuration files.
  32. What are the Hive data model's components?
  33. In MySQL’s table column, how will you search for a particular string?
  34. What do you mean by a .hiverc file in MySQL?
  35. Create a statement in MySQL that generates a number of objects. Name these objects.
  36. What is Rack Awareness?
  37. Can you describe binary classification?
  38. Does Uber create traffic congestion?
  39. How can you calculate Uber Pool’s radius in a city?
  40. How can you model the cost of renting cars to drivers?
  41. Explain PCA, equations, and assumptions
  42. How will you decide if Uber Pool should include a location?
  43. Does congestion and driving conditions impact rider’s experience and Uber’s revenue?
  44. Can you explain the workings of Uber’s surge pricing algorithm? How can you ascertain the best strategy?
  45. Define CLT. Do you think it is relevant for Uber?

5 Tips to Prepare for Your Uber Data Engineer Interview

Interview prep can be daunting, especially when your gunning for a tier-1 tech company like Uber. However, with a well-planned prep strategy, you will be able to ace that interview. Here are the four key components that your preparation should include:

Keep Your Elevator Pitch Ready

Equip yourself with a crisp elevator pitch. It should include vital details about your background, skills, and previous experience. Moreover, remember to highlight your contribution in the preceding job role. Additionally, make sure that you communicate your motivations to work with Uber adequately. 

Review the Fundamentals of Computer Science

Make sure that your fundamentals of computer science are not rusty during the interview. For this, refresh your knowledge of data structures and algorithms. Needless to say, this knowledge will come in handy when solving practical problems. 

Develop Solutions for Working Problems

At the interview, you can expect several real-life engineering challenges. To prepare, solve as many programming practice problems as you can. You can take this prep up a notch and give yourself a time limit of 30 minutes, which will simulate a realistic interview.  Remember: Uber assesses how well you translate thoughts into code.

Prepare to Communicate With Your Interviewer

When faced with a problem, do not hesitate to communicate with the interviewer and asking clarifying questions. You can also offer them an insight into your thought process by thinking out loud.

Enroll in a Data Engineering Interview Bootcamp

Top tech companies receive a myriad of applications each year, and Uber is no exception. If you wish to stand out from the competition, join Interview Kickstart. Our Data Engineering Masterclass is a first-of-its-kind interview prep program tailored to help data engineers nail the toughest interviews at FAANG and other tier-1 tech companies like Uber. 

Our interview prep comprises a comprehensive curriculum along with technical coaching and mock interviews conducted by tech leads and hiring managers from FAANG+ companies, which will help you ace your Uber interview with ease. 

Sign up for our FREE webinar to learn more. 

FAQs on Uber and Data Engineering 

  1. How much money does a data engineer make?
    In the US, a data engineer’s average salary is $127,601 per annum.
  2. How many engineers work at Uber?
    Uber currently has more than 6,000 employees, among which 2,000 are engineers.

What do Uber data engineers do?
The data engineering team develops, tests, and maintains infrastructures for Uber’s data generation. They create data pipelines and connect data from one system to another.

Worried About Failing Tech Interviews?

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Founder, Interview Kickstart
Our tried & tested strategy for cracking interviews
How FAANG hiring process works
The 4 areas you must prepare for
How you can accelerate your learnings
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