UBS Data Engineer Interview Questions + Guide in 2024

UBS is the world’s largest global wealth manager, operating through four business divisions: Global Wealth Management, Personal & Corporate Banking, Asset Management, and the Investment Bank. With over 50 countries and over 70,000 employees, UBS stands out in all major financial centers.

In this guide, we’ll walk you through the interview process, some commonly asked UBS Data Engineer interview questions, and provide valuable tips. Let’s get started!

The interview process usually depends on the role and seniority, however, you can expect the following on a UBS data engineer interview:

Culture and Aptitude Tests

Once your application has been selected, you will be required to complete a culture test and an aptitude test within 5 days. These tests assess whether your values align with UBS’s core principles and evaluate your analytical skills and problem-solving abilities.

HR Screening Interview

After successfully navigating the initial tests, you will proceed to an HR screening interview. This will involve a series of standard questions aimed at understanding your background, key experiences, and skill levels. Be prepared to answer questions like “How would you respond to realizing that you may be in danger of missing a client’s deadline?” and to discuss your capabilities in a clear and concise manner.

Technical Interview Rounds

The technical interview process at UBS for a Data Engineer position consists of several stages:

1. Initial Technical Screening:

   • This interview will cover core data engineering concepts, your past experiences, and specific questions related to your technical skills, such as:
     • How does Python differ from other languages?
     • What is a Bloom filter?

2. Technical Challenge:

   • You’ll face a series of progressive Python problems (e.g., palindrome, anagram) and one SQL coding problem aimed at assessing your problem-solving skills and technical capabilities.

3. Interviews with Manager and Lead Engineers:

   • These include in-depth discussions on data engineering concepts, coding challenges, and questions about your hands-on experience with data pipelines, cloud technologies, and large distributed systems.

Onsite Interview Rounds

If you proceed past the initial technical stages, you will be called in for onsite interviews:

• Hiring Team Discussions: The sessions will involve a mix of behavioral and technical questions designed to gauge your fit within the team and your technical prowess.

• Final Technical Assessment: Even though the onsite interview process does not typically include live coding assessments, be prepared for detailed discussions on your past projects, especially those involving Python, SQL, Spark, and cloud technologies.

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

1. Write a function search_list to check if a target value is in a linked list.

Write a function, search_list, that returns a boolean indicating if the target value is in the linked_list or not. You receive the head of the linked list, which is a dictionary with the keys value and next. If the linked list is empty, you’ll receive None.

2. Write a query to find users who placed less than 3 orders or ordered less than $500 worth of product.

Write a query to identify the names of users who placed less than 3 orders or ordered less than $500 worth of product. Use the transactions, users, and products tables.

3. Create a function digit_accumulator to sum every digit in a string representing a floating-point number.

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.

4. Develop a function to parse the most frequent words used in poems.

You’re hired by a literary newspaper to parse the most frequent words used in poems. Poems are given as a list of strings called sentences. Return a dictionary of the frequency that words are used in the poem, processed as lowercase.

5. Write a function rectangle_overlap to determine if two rectangles overlap.

You are given two rectangles a and b each defined by four ordered pairs denoting their corners on the x, y plane. Write a function rectangle_overlap to determine whether or not they overlap. Return True if so, and False otherwise.

6. What are the Z and t-tests, and when should you use each?

Explain the purpose and differences between Z and t-tests. Describe scenarios where one test is preferred over the other.

7. What are the drawbacks of the given data layouts, and how would you reformat them?

Analyze the provided student test score datasets for potential issues. Suggest formatting changes to make the data more useful for analysis. Discuss common problems in “messy” datasets.

8. What metrics would you use to determine the value of each marketing channel?

Given data on marketing channels and costs, identify key metrics to evaluate the value of each channel for a company selling B2B analytics dashboards.

9. How would you determine the next partner card based on customer spending data?

Using customer spending data, outline a method to identify the best potential partner for a new credit card offering.

10. How would you investigate if the redesigned email campaign led to the increase in conversion rates?

Given a rise in new-user to customer conversion rates after a redesign, determine if the increase is due to the new email campaign or other factors. Describe your investigative approach.

11. Which model would perform better for predicting Airbnb booking prices: linear regression or random forest regression?

You need to build a model to predict booking prices on Airbnb. Compare linear regression and random forest regression to determine which model would perform better and explain why.

12. How would you design a function to detect anomalies in univariate and bivariate datasets?

If given a univariate dataset, how would you design a function to detect anomalies? What if the data is bivariate?

13. What is the expected churn rate in March for customers who bought subscriptions since January 1st?

You noticed that 10% of customers who bought subscriptions in January 2020 canceled before February 1st. Assuming uniform new customer acquisition and a 20% month-over-month decrease in churn, what is the expected churn rate in March for all customers who bought the product since January 1st?

14. How would you explain a p-value to a non-technical person?

How would you explain what a p-value is to someone who is not technical?

You should plan to brush up on any technical skills and try as many practice interview questions and mock interviews as possible. A few tips for acing your UBS data engineer interview include:

• Know UBS’s Core Values: Thoroughly understand UBS’s values and culture. Prepare to discuss how your personal values align with those of UBS, especially regarding collaboration and innovation.
• Brush Up on Fundamental Concepts: Be well-prepared with your knowledge of Python, SQL, cloud technologies like Azure, and data engineering principles. Exercise your problem-solving capabilities, as you will handle both conceptual and applied questions.
• Stay Professional in All Interactions: Even if you decide to decline the offer, always communicate professionally. Lack of courtesy can leave a negative impression.

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

According to Glassdoor, data engineer at UBS earn between $122K to $168K per year, with an average of $145K per year.

What qualities and skills is UBS looking for in a Data Engineer?

UBS seeks candidates with strong skills in data preparation, text analytics, and data visualization. Expertise in SQL, Python, and other software applications is crucial. Experience in handling business-wide reporting, conducting system-wide audits, and managing regulatory change projects is also highly valued.

What sets UBS apart from other financial institutions?

UBS is the world’s largest and only truly global wealth manager, operating through four diverse business divisions. The company’s global infrastructure and purpose-led culture promote flexible working arrangements, innovation, and collaboration, making UBS a unique place to work.

How does UBS support professional growth and work-life balance?

At UBS, flexible work arrangements such as part-time, job-sharing, and hybrid working are embraced. The company’s culture supports new experiences, skills acquisition, and continuous learning. UBS also values diverse backgrounds, perspectives, and experiences, which contribute to the company’s overall success.

As you prepare to become a Data Engineer at UBS, it’s clear that the pathway is rigorous, thorough, and designed to identify top talent. From the initial culture and aptitude tests to the nuanced technical and problem-solving questions, the process is tailored to evaluate your fit within UBS’s environment. Despite varied interview experiences, what stands out is UBS’s dedication to fostering a diverse, collaborative, and innovative workplace.

If you want more insights about the company, check out our main UBS Interview Guide, where we have covered many interview questions that could be asked. Additionally, explore our interview guides for other roles such as software engineer and data analyst to learn more about UBS’s interview process for different positions.

Good luck with your interview!