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:
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:
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:
Alongside a solid foundation in software engineering, you must also be well-versed with the following:
In addition to technical skills, you should also have these soft skills in your arsenal:
Uber has a dedicated data science and analytics team that transforms data about these areas of its business:
Uber’s interview is a 4-step process, which comprises the following:
Read the Uber Tech Interview Process article for more information.
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.
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.
Input:
Sentence: that cattle is rattled by the battery
roots = [“cat,†“bat,†“ratâ€]
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,†“ratâ€]
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:
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. 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:
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:
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:
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:
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:
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.
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.
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. Â Remember: Uber assesses how well you translate thoughts into code.
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.
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.
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.
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