UCLA Health Data Engineer Interview Questions + Guide in 2025

UCLA Health is a leading academic health system dedicated to advancing healthcare through innovative research, education, and clinical practice.

As a Data Engineer at UCLA Health, you will play a pivotal role in designing and developing data warehouse architecture tailored for a university medical system. Key responsibilities include creating extraction, transformation, and load (ETL) standards, guiding the management and enhancement of data warehouses, and setting enterprise standards for data objects. You will also provide technical support in ETL processes, logical and physical data structures, and data modeling, while mentoring junior developers. The ideal candidate will possess a solid foundation in data integration and transformation platforms, experience managing academic data, and proficiency in programming languages such as SQL, Python, and SAS. A strong ability to communicate complex technical concepts to diverse audiences is essential, as is a commitment to fostering a collaborative and inclusive work environment, aligning with UCLA Health’s values of innovation and excellence in patient care.

This guide will empower you to prepare effectively for an interview by providing insights into the expectations of the role and the company culture, allowing you to present your most relevant skills and experiences confidently.

The interview process for a Data Engineer position at UCLA Health is structured to assess both technical skills and cultural fit within the organization. It typically consists of several key stages:

1. Initial Screening

The process begins with an initial screening call, usually conducted by an associate director or recruiter. This conversation is generally focused on your background, experience, and understanding of the role. Expect to discuss your technical skills, particularly in areas relevant to data engineering, as well as your motivations for applying to UCLA Health. This is also an opportunity for you to learn more about the company culture and the specifics of the position.

2. Technical Assessment

Following the initial screening, candidates are often required to complete a technical assessment. This assessment may involve practical exercises related to data extraction, transformation, and loading (ETL) processes, as well as questions about data modeling and database management. Candidates should be prepared to explain their thought processes and methodologies during this assessment, as evaluators will be interested in understanding how you approach problem-solving in a technical context.

3. Panel Interview

The next step typically involves a panel interview, where candidates meet with multiple team members, including data engineers and possibly other stakeholders. This interview format allows for a comprehensive evaluation of your technical abilities, teamwork skills, and cultural fit. Questions may cover your experience with specific tools and technologies, such as SQL, SAS, and ETL frameworks, as well as your ability to communicate complex concepts to both technical and non-technical audiences.

4. Final Interview

The final stage of the interview process usually involves a conversation with a higher-level director or manager. This interview focuses on the strategic aspects of the role, including how you would contribute to the data architecture and data warehouse management at UCLA Health. Expect to discuss your vision for the role, your leadership style, and how you would mentor junior developers. This is also a chance for you to ask more in-depth questions about the team and the organization.

As you prepare for your interview, consider the types of questions that may arise in each of these stages.

Here are some tips to help you excel in your interview.

Understand the Technical Requirements

Familiarize yourself with the specific technologies and methodologies mentioned in the job description, such as ETL processes, data warehousing, and the various database management systems like MSSQL, MySQL, and Oracle DB. Be prepared to discuss your experience with these tools in detail, including any challenges you've faced and how you overcame them. Highlight your proficiency in programming languages like SQL, Python, and SAS, as these are crucial for the role.

Prepare for Assessments

Expect to undergo technical assessments during the interview process, particularly focused on SAS and data manipulation. Practice common SAS procedures and be ready to explain your thought process and methodologies clearly. This will not only demonstrate your technical skills but also your ability to communicate complex concepts effectively, which is essential in a collaborative environment.

Showcase Leadership and Mentorship Skills

As the role involves leading and mentoring junior developers, be prepared to discuss your leadership experiences. Share specific examples of how you've guided team members, resolved conflicts, or contributed to team success. This will show your potential to foster a positive team culture and drive project success.

Be Ready for Behavioral Questions

Given the feedback from previous candidates, expect a mix of technical and behavioral questions. Prepare to articulate your experiences and how they align with UCLA Health's values. Reflect on your past roles and be ready to discuss how you've handled challenges, worked in teams, and contributed to organizational goals.

Emphasize Cultural Fit

While the interviewers may come across as stiff, it's important to convey your enthusiasm for the role and the organization. Research UCLA Health's mission and values, and think about how your personal values align with theirs. This will help you articulate why you are a good fit for the team and the organization as a whole.

Follow Up Professionally

After the interview, send a thoughtful thank-you email to express your appreciation for the opportunity to interview. Reiterate your interest in the position and briefly mention a key point from the interview that resonated with you. This not only shows professionalism but also keeps you top of mind for the interviewers.

By following these tips, you can present yourself as a well-rounded candidate who is not only technically proficient but also a great cultural fit for UCLA Health. Good luck!

In this section, we’ll review the various interview questions that might be asked during a Data Engineer interview at UCLA Health. The interview process will likely assess your technical skills in data engineering, your experience with data warehousing, and your ability to communicate complex concepts to both technical and non-technical stakeholders. Be prepared to demonstrate your knowledge of ETL processes, database management, and your proficiency in relevant programming languages.

Technical Skills

1. What ETL tools have you used, and can you describe a project where you implemented ETL processes?

This question aims to assess your hands-on experience with ETL tools and your ability to apply them in real-world scenarios.

How to Answer

Discuss specific ETL tools you have used, the context of the project, and the challenges you faced. Highlight your role in the project and the impact of your work.

Example

“I have extensive experience with SSIS and Azure Data Factory. In my previous role, I led a project to migrate data from legacy systems to a new data warehouse. I designed the ETL processes to ensure data integrity and optimized the workflows, which reduced processing time by 30%.”

2. Can you explain the difference between logical and physical data models?

This question tests your understanding of data modeling concepts, which are crucial for a Data Engineer.

How to Answer

Define both terms clearly and explain their significance in the data architecture process. Provide examples of when you would use each type of model.

Example

“Logical data models represent the abstract structure of the data, focusing on the relationships and constraints without considering how the data will be physically stored. Physical data models, on the other hand, detail how the data will be stored in the database, including data types and indexing strategies. I typically start with a logical model to outline the data requirements before moving to the physical model for implementation.”

3. Describe your experience with SQL and any advanced SQL techniques you have used.

This question evaluates your proficiency in SQL, which is essential for data manipulation and querying.

How to Answer

Mention specific SQL techniques you are familiar with, such as joins, subqueries, or window functions, and provide examples of how you have used them in your work.

Example

“I am proficient in SQL and have used advanced techniques like window functions and CTEs to analyze large datasets. For instance, I used window functions to calculate running totals for financial reports, which allowed the team to gain insights into trends over time.”

4. How do you ensure data quality and integrity in your data engineering processes?

This question assesses your approach to maintaining high standards in data management.

How to Answer

Discuss the methods and tools you use to validate data, monitor data quality, and address any issues that arise.

Example

“I implement data validation checks at various stages of the ETL process, such as ensuring data types match and checking for duplicates. Additionally, I use automated monitoring tools to track data quality metrics and set up alerts for any anomalies, allowing for quick resolution.”

Data Warehousing

5. What experience do you have with data warehousing methodologies?

This question aims to gauge your familiarity with data warehousing concepts and practices.

How to Answer

Explain the methodologies you have used, such as Kimball or Inmon, and how they influenced your work in data warehousing.

Example

“I have primarily worked with the Kimball methodology, focusing on dimensional modeling to create user-friendly data marts. In my last project, I designed a star schema for a healthcare data warehouse, which improved query performance and made it easier for analysts to access the data they needed.”

6. Can you describe a challenging data integration project you worked on?

This question seeks to understand your problem-solving skills and experience with complex data integration tasks.

How to Answer

Outline the project, the challenges you faced, and the solutions you implemented to overcome those challenges.

Example

“I worked on a project that required integrating data from multiple sources, including SQL databases and flat files. The main challenge was ensuring data consistency across these sources. I developed a robust ETL process that included data cleansing steps and established a master data management strategy, which significantly improved data accuracy.”

7. How do you approach performance tuning in a data warehouse environment?

This question assesses your ability to optimize data warehouse performance.

How to Answer

Discuss the techniques you use for performance tuning, such as indexing, partitioning, or query optimization.

Example

“I regularly analyze query performance and identify slow-running queries. I use indexing and partitioning strategies to improve access times. For example, I partitioned large tables based on date ranges, which reduced query execution time by over 50%.”

8. What strategies do you use for backing up and securing databases?

This question evaluates your understanding of database security and backup practices.

How to Answer

Explain the backup strategies you implement and the security measures you take to protect sensitive data.

Example

“I implement a multi-tiered backup strategy that includes full, differential, and transaction log backups to ensure data recovery. For security, I enforce role-based access controls and regularly audit user permissions to protect sensitive information.”

Communication and Collaboration

9. How do you communicate technical concepts to non-technical stakeholders?

This question assesses your ability to bridge the gap between technical and non-technical team members.

How to Answer

Describe your approach to simplifying complex concepts and ensuring understanding among diverse audiences.

Example

“I focus on using analogies and visual aids to explain technical concepts. For instance, when discussing data flow, I use flowcharts to illustrate the process, which helps non-technical stakeholders grasp the information more easily.”

10. Describe a time when you had to collaborate with a cross-functional team. What was your role?

This question evaluates your teamwork and collaboration skills.

How to Answer

Share a specific example of a project where you worked with different teams, highlighting your contributions and the outcome.

Example

“I collaborated with the finance and IT teams on a project to develop a new reporting dashboard. My role was to gather requirements from the finance team and translate them into technical specifications for the IT team. This collaboration resulted in a dashboard that met the needs of both teams and improved reporting efficiency.”