University Of Michigan Data Engineer Interview Questions + Guide in 2025

The University of Michigan is a leading institution dedicated to advancing knowledge and improving human-computer interactions through innovative technology solutions.

As a Data Engineer at the University of Michigan, you will play a pivotal role in developing and managing data systems that support public health initiatives, particularly in response to COVID-19. Your key responsibilities will include designing and implementing secure data pipelines to manage large datasets, utilizing cloud technologies like Amazon Web Services (AWS) for storage and processing, and writing code using languages such as Python and Rust. You will collaborate with public health officials, data scientists, and IT teams to understand project requirements and create tailored solutions that drive impactful insights. A strong foundation in public health principles is essential to interpret and transform health-related data effectively. The ideal candidate will possess a Bachelor's degree in Computer Science, experience in building data pipelines and backend services, and familiarity with Extract, Transform, Load (ETL) processes.

This guide is designed to help you prepare thoroughly for your interview, equipping you with insights into the role's expectations and the types of questions you may encounter, ultimately increasing your chances of success.

The interview process for a Data Engineer position at the University of Michigan is designed to assess both technical skills and cultural fit within the organization. It typically consists of multiple rounds, each focusing on different aspects of the candidate's qualifications and experiences.

1. Initial Screening

The process begins with an initial screening, which is often a brief phone interview with a recruiter or hiring manager. This conversation usually lasts around 30 minutes and serves to gauge your interest in the position, discuss your background, and assess your fit for the role. Expect questions about your experience with data engineering, programming languages, and familiarity with public health principles.

2. Technical Interview

Following the initial screening, candidates typically participate in a technical interview. This round may involve a video call with one or more technical team members. Here, you will be asked to demonstrate your proficiency in relevant technologies such as AWS, Python, and Rust. You may also be required to discuss your experience with building data pipelines, APIs, and backend services. Be prepared to solve coding problems or discuss your approach to data management and processing.

3. Behavioral Interview

The next step often includes a behavioral interview, which may involve multiple interviewers from different teams. This round focuses on understanding how you work within a team, manage competing priorities, and handle conflicts. Expect questions that require you to provide specific examples from your past experiences, showcasing your problem-solving skills and ability to collaborate with diverse groups, including public health officials and data scientists.

4. Presentation Round

In some cases, candidates may be invited to a presentation round, where you will present a project or a relevant topic to a panel of interviewers. This is an opportunity to demonstrate your communication skills and your ability to convey complex technical information to non-technical stakeholders. Be prepared to answer questions about your presentation and discuss how your work aligns with the goals of the department.

5. Final Interview

The final interview may involve a more casual conversation with potential peers or team members. This round is designed to assess cultural fit and provide you with a chance to ask questions about the team dynamics and work environment. It’s a good opportunity to express your enthusiasm for the role and the organization.

Throughout the interview process, candidates should be ready to discuss their technical skills, project experiences, and how they can contribute to the University of Michigan's mission in public health data analysis and visualization.

Next, let’s explore the types of questions you might encounter during these interviews.

In this section, we’ll review the various interview questions that might be asked during a Data Engineer interview at the University of Michigan. The interview process will likely focus on your technical skills, experience with data systems, and your ability to work collaboratively with diverse teams. Be prepared to discuss your knowledge of public health principles, as well as your proficiency in relevant technologies such as AWS, Python, and Rust.

Technical Skills

1. Can you describe your experience with AWS and how you have utilized it in your previous projects?

Understanding your experience with AWS is crucial, as it is a key component of the role.

How to Answer

Discuss specific AWS services you have used, such as S3 or Lambda, and how they contributed to the success of your projects.

Example

“I have utilized AWS S3 for scalable data storage in my previous role, where I managed large datasets for a public health initiative. By implementing Lambda functions, I was able to automate data processing tasks, which significantly reduced the time required for data ingestion and analysis.”

2. What is your experience with data pipeline development? Can you walk us through a project where you built a data pipeline?

This question assesses your hands-on experience with data engineering tasks.

How to Answer

Provide a detailed overview of a specific project, including the technologies used, challenges faced, and how you overcame them.

Example

“In my last position, I developed a data pipeline using Python and AWS services to process COVID-19 vaccination data. I implemented ETL processes to extract data from state databases, transform it for analysis, and load it into a secure data warehouse. This pipeline improved data accessibility for public health officials.”

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

Data quality is critical in public health data analysis.

How to Answer

Discuss your approach to data validation and any tools or techniques you use to maintain data integrity.

Example

“I implement rigorous data validation checks at each stage of the ETL process. For instance, I use automated scripts to identify and correct anomalies in the data before it is loaded into the database. This ensures that the data used for analysis is accurate and reliable.”

4. Can you explain the Extract, Transform, Load (ETL) process and its importance?

This question tests your foundational knowledge of data engineering concepts.

How to Answer

Define ETL and explain its significance in data management.

Example

“ETL is a process that involves extracting data from various sources, transforming it into a suitable format, and loading it into a target database. It is essential for ensuring that data is clean, consistent, and ready for analysis, which is particularly important in public health data where decisions are made based on this information.”

5. What programming languages are you proficient in, and how have you applied them in your work?

This question assesses your technical skills in programming.

How to Answer

Mention the languages you are proficient in, particularly Python and Rust, and provide examples of how you have used them.

Example

“I am proficient in Python and Rust. In my previous role, I used Python for data manipulation and analysis, leveraging libraries like Pandas and NumPy. I also developed backend services in Rust to ensure high performance and security in data processing tasks.”

Behavioral Questions

1. Describe a time when you had to manage competing priorities. How did you handle it?

This question evaluates your time management and prioritization skills.

How to Answer

Share a specific example that demonstrates your ability to prioritize tasks effectively.

Example

“In a previous project, I was tasked with developing a data pipeline while also preparing a presentation for stakeholders. I prioritized the pipeline development by breaking it down into manageable tasks and setting clear deadlines, which allowed me to complete both on time without compromising quality.”

2. How do you approach collaboration with cross-functional teams?

Collaboration is key in a role that involves working with public health officials and data scientists.

How to Answer

Discuss your communication style and how you ensure effective collaboration.

Example

“I believe in maintaining open lines of communication with all team members. In my last project, I scheduled regular check-ins with public health officials to gather their input and ensure that the data solutions I was developing met their needs. This collaborative approach led to a successful project outcome.”

3. Tell me about a particularly challenging project you worked on. What made it challenging and how did you overcome those challenges?

This question assesses your problem-solving skills and resilience.

How to Answer

Provide a specific example of a challenging project and the steps you took to address the difficulties.

Example

“I worked on a project that involved integrating multiple data sources for a public health initiative. The challenge was reconciling different data formats and ensuring data consistency. I overcame this by developing a comprehensive data mapping strategy and collaborating closely with the data providers to standardize the data before integration.”

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

This question gauges your commitment to professional development.

How to Answer

Share the resources you use to stay informed about industry trends.

Example

“I regularly read industry blogs, participate in online forums, and attend webinars related to data engineering. I also take online courses to learn new technologies, such as recent advancements in cloud computing and data processing frameworks.”

5. Why are you interested in this position at the University of Michigan?

This question assesses your motivation and alignment with the organization’s mission.

How to Answer

Express your enthusiasm for the role and how it aligns with your career goals and values.

Example

“I am passionate about using data to improve public health outcomes, and I admire the University of Michigan’s commitment to innovative solutions in this field. This position offers the opportunity to work on impactful projects that directly contribute to community health, which aligns perfectly with my career aspirations.”