Under Armour Data Engineer Interview Questions + Guide in 2025

Under Armour is dedicated to empowering those who strive for more, guided by values that promote sustainability, teamwork, and inclusivity.

As a Data Engineer at Under Armour, you will play a crucial role in designing, implementing, and maintaining a modern data platform that supports the company's strategic goals. Your key responsibilities will include developing robust data models, creating visualizations, and ensuring data integrity across various business units. The ideal candidate will possess strong skills in SQL, data architecture, and data transformation, along with experience in analytical reporting tools like Tableau and data orchestration platforms such as DBT. You will collaborate closely with cross-functional teams to translate business requirements into technical solutions, fostering a culture of self-service reporting and data-driven decision-making.

This guide is designed to equip you with the knowledge and insights needed to excel in your interview, helping you articulate your skills and experiences in a way that aligns with Under Armour's mission and values.

The interview process for a Data Engineer at Under Armour is structured to assess both technical skills and cultural fit within the company. It typically consists of several stages designed to evaluate your expertise in data engineering, your problem-solving abilities, and your alignment with Under Armour's values.

1. Initial Phone Screen

The process begins with an initial phone screen, usually lasting about 30 minutes. This call is typically conducted by a recruiter from the HR team. During this conversation, you will be asked to introduce yourself and discuss your background, skills, and experiences relevant to the Data Engineer role. The recruiter will also provide insights into Under Armour's culture and values, ensuring that you understand the company's commitment to empowering athletes and promoting sustainability.

2. Technical Assessment

Following the initial screen, candidates are often required to complete a technical assessment. This may involve a take-home assignment where you will be tasked with demonstrating your data modeling, SQL proficiency, and data transformation skills. The assignment is designed to evaluate your ability to design and implement data solutions that meet business requirements. You may also be asked to showcase your experience with data visualization tools, such as Tableau, and your understanding of data architecture.

3. Final Interview Rounds

The final stage of the interview process typically consists of multiple rounds of interviews with team members and stakeholders. These interviews may be conducted via video conferencing and will focus on both technical and behavioral aspects. You can expect to discuss your previous projects, your approach to data engineering challenges, and how you collaborate with cross-functional teams. Additionally, interviewers will assess your understanding of data governance, ETL processes, and your ability to educate and empower business users in a self-service reporting model.

As you prepare for these interviews, it's essential to be ready to discuss your technical skills in detail, as well as how you embody Under Armour's core values.

Next, let's explore the specific interview questions that candidates have encountered during this process.

In this section, we’ll review the various interview questions that might be asked during a Data Engineer interview at Under Armour. The interview process will likely focus on your technical skills, problem-solving abilities, and how well you can collaborate with cross-functional teams. Be prepared to discuss your experience with data modeling, SQL, ETL processes, and visualization tools, as well as your approach to ensuring data quality and performance.

Technical Skills

1. Can you explain the ETL process and how you have implemented it in your previous projects?

Understanding the ETL (Extract, Transform, Load) process is crucial for a Data Engineer, as it is fundamental to data integration and management.

How to Answer

Discuss your experience with each stage of the ETL process, emphasizing any specific tools you have used and the challenges you faced. Highlight how you ensured data quality and performance during the process.

Example

“In my previous role, I implemented an ETL process using Apache NiFi. I extracted data from various sources, transformed it to meet our reporting needs, and loaded it into our Snowflake data warehouse. I faced challenges with data consistency, which I addressed by implementing validation checks during the transformation phase.”

2. Describe your experience with SQL and how you have used it to solve complex data problems.

SQL is a critical skill for data engineers, and interviewers will want to know how you leverage it in your work.

How to Answer

Provide specific examples of complex queries you have written, the problems they solved, and any performance optimizations you implemented.

Example

“I have extensive experience with SQL, particularly in writing complex joins and subqueries to extract insights from large datasets. For instance, I optimized a query that aggregated sales data across multiple regions, reducing the execution time from several minutes to under 30 seconds by indexing key columns.”

3. How do you ensure data quality and integrity in your data models?

Data quality is paramount in data engineering, and interviewers will want to know your strategies for maintaining it.

How to Answer

Discuss the methods you use to validate data, monitor data quality, and handle discrepancies. Mention any tools or frameworks you have used.

Example

“I ensure data quality by implementing automated validation checks during the ETL process. I also use tools like Great Expectations to monitor data integrity continuously. When discrepancies arise, I investigate the root cause and work with the data source teams to resolve the issues promptly.”

4. Can you walk us through a data modeling project you have completed?

Data modeling is a key responsibility for a Data Engineer, and interviewers will want to understand your approach.

How to Answer

Describe the project, your role, the tools you used, and the outcome. Focus on how you designed the data model to meet business requirements.

Example

“I led a data modeling project for a retail client where I designed a star schema to support their sales analytics. I used Snowflake for the data warehouse and DBT for transformation. The model improved query performance and provided the business with actionable insights into customer purchasing behavior.”

Data Visualization

5. What experience do you have with data visualization tools, and how have you used them to communicate insights?

Data visualization is essential for presenting data findings effectively, and interviewers will want to know your proficiency with these tools.

How to Answer

Discuss the visualization tools you have used, the types of dashboards you created, and how they impacted decision-making.

Example

“I have worked extensively with Tableau to create interactive dashboards for our marketing team. One dashboard I developed tracked campaign performance in real-time, allowing the team to make data-driven adjustments quickly, which ultimately increased our ROI by 15%.”

6. How do you approach gathering requirements from stakeholders for a reporting solution?

Understanding stakeholder needs is crucial for delivering effective data solutions.

How to Answer

Explain your process for engaging with stakeholders, gathering requirements, and translating them into technical specifications.

Example

“I typically start by conducting interviews with stakeholders to understand their needs and pain points. I then create mockups of potential reporting solutions and gather feedback to ensure alignment before moving forward with development.”

7. Describe a challenge you faced while working on a data project and how you overcame it.

Problem-solving is a key skill for Data Engineers, and interviewers will want to see how you handle challenges.

How to Answer

Share a specific challenge, your thought process in addressing it, and the outcome of your actions.

Example

“During a project, we encountered significant performance issues with our data pipeline. I conducted a thorough analysis and identified bottlenecks in the transformation process. By optimizing our SQL queries and implementing parallel processing, I was able to reduce the processing time by 50%.”

8. How do you stay updated with the latest trends and technologies in data engineering?

Continuous learning is important in the tech field, and interviewers will want to know how you keep your skills current.

How to Answer

Discuss the resources you use to stay informed, such as online courses, webinars, or industry publications.

Example

“I regularly follow industry blogs and participate in webinars to stay updated on the latest trends in data engineering. I also take online courses on platforms like Coursera to learn about new tools and technologies, ensuring that my skills remain relevant.”