Premier Inc. Data Engineer Interview Questions + Guide in 2025

Premier Inc. is a leading healthcare improvement company that strives to transform the industry through innovative solutions and collaborative efforts among healthcare providers.

As a Data Engineer at Premier Inc., you will play a crucial role in managing the acquisition, storage, modeling, and presentation of data to ensure it is accessible and reliable for a wide range of analytical use cases. Key responsibilities include building and optimizing data pipelines and workflows, utilizing modern data storage technologies, and ensuring data integrity while interacting with various stakeholders. A strong understanding of SQL, scripting languages (preferably Python), and experience with data orchestration tools like Apache Airflow or Google Cloud Composer are essential for success in this role. Additionally, you will be expected to support the solutions you develop through user training and proactive issue resolution, all while driving efficiency and innovation in data management practices.

The ideal candidate for this position will be an independent thinker with a passion for problem-solving, eager to explore new technologies and continuously enhance their skillset. This guide will help you prepare for your interview by providing insights into the skills and traits that Premier values, allowing you to demonstrate your fit and readiness for the Data Engineer role.

The interview process for a Data Engineer at Premier Inc. is designed to assess both technical skills and cultural fit within the organization. It typically consists of three main stages, each focusing on different aspects of the candidate's qualifications and compatibility with the company.

1. Initial Screening

The process begins with an initial screening, which is often conducted via a phone interview with a recruiter. This conversation usually lasts around 30-45 minutes and serves to gauge your interest in the role, discuss your background, and evaluate your fit for Premier's culture. The recruiter may ask about your experience with data engineering concepts, tools, and technologies, as well as your motivation for applying to Premier.

2. Technical Assessment

Following the initial screening, candidates typically undergo a technical assessment. This may include a take-home coding test or a live coding session where you will be asked to solve problems related to data extraction, transformation, and loading (ETL) processes. Expect to demonstrate your proficiency in SQL, Python, and data pipeline orchestration tools. You may also be asked to discuss your approach to building efficient data models and optimizing data storage solutions.

3. Panel Interview

The final stage of the interview process is usually a panel interview, which may take place in person or virtually. During this round, you will meet with multiple team members, including supervisors and peers. The panel will assess your technical knowledge, problem-solving abilities, and how well you align with the team's values and goals. Behavioral questions will also be a significant part of this round, focusing on your past experiences and how you handle challenges in a collaborative environment.

As you prepare for your interview, it's essential to be ready for a variety of questions that will test both your technical expertise and your ability to work within a team.

In this section, we’ll review the various interview questions that might be asked during a Data Engineer interview at Premier Inc. The interview process will likely focus on your technical skills, particularly in SQL, data engineering concepts, and your ability to work collaboratively in an Agile environment. Be prepared to discuss your experience with data pipelines, data storage solutions, and your approach to problem-solving.

Technical Skills

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

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

How to Answer

Discuss your experience with ETL processes, the tools you used, and any challenges you faced during implementation. Highlight your ability to optimize these processes for efficiency.

Example

“In my previous role, I implemented an ETL process using Apache Airflow to automate data extraction from various sources, transform it using Python scripts, and load it into a data warehouse. I faced challenges with data quality, which I addressed by implementing validation checks during the transformation phase, ensuring that only clean data was loaded.”

2. Describe your experience with SQL. What are some complex queries you have written?

SQL is a key skill for Data Engineers, and demonstrating your proficiency can set you apart.

How to Answer

Provide specific examples of complex SQL queries you have written, including joins, subqueries, and window functions. Discuss the context in which you used these queries.

Example

“I have extensive experience with SQL, including writing complex queries for data analysis. For instance, I created a query that involved multiple joins and window functions to calculate the running total of sales over time, which was crucial for our monthly reporting.”

3. What tools have you used for data orchestration, and how do you choose the right one for a project?

Data orchestration tools are essential for managing data workflows, and your familiarity with them is important.

How to Answer

Discuss the tools you have used, such as Apache Airflow or Google Cloud Composer, and explain your decision-making process for selecting a tool based on project requirements.

Example

“I have used Apache Airflow for orchestrating data workflows due to its flexibility and scalability. When choosing a tool, I consider factors like the complexity of the workflows, team familiarity, and integration capabilities with our existing systems.”

4. Can you explain the differences between a data warehouse and a data lake?

Understanding the distinctions between these two data storage solutions is vital for a Data Engineer.

How to Answer

Clearly define both concepts and discuss scenarios where one might be preferred over the other.

Example

“A data warehouse is structured for analytical queries and reporting, while a data lake stores raw data in its native format, allowing for more flexibility. I typically recommend a data lake for unstructured data and a data warehouse for structured data that requires complex queries.”

5. How do you ensure data quality and integrity in your data pipelines?

Data quality is critical in data engineering, and your approach to maintaining it will be scrutinized.

How to Answer

Discuss the methods you use to validate and clean data, as well as any tools or frameworks that assist in this process.

Example

“I ensure data quality by implementing validation checks at each stage of the data pipeline. I use tools like Great Expectations to automate data validation and monitor data quality metrics, which helps in identifying issues early in the process.”

Behavioral Questions

1. Describe a time when you faced a significant challenge in a project. How did you overcome it?

This question assesses your problem-solving skills and resilience.

How to Answer

Share a specific example, focusing on the challenge, your approach to resolving it, and the outcome.

Example

“In a previous project, we faced a major delay due to unexpected data source changes. I organized a meeting with stakeholders to realign our goals and quickly adapted our data pipeline to accommodate the new source, which allowed us to meet our deadline.”

2. How do you prioritize tasks when working on multiple projects?

Time management and prioritization are key skills for a Data Engineer.

How to Answer

Explain your approach to prioritizing tasks, including any tools or methodologies you use.

Example

“I prioritize tasks based on project deadlines and impact. I use project management tools like Jira to track progress and ensure that I focus on high-impact tasks first, while also allowing for flexibility to address urgent issues as they arise.”

3. Can you give an example of how you have worked collaboratively in a team?

Collaboration is essential in an Agile environment, and your ability to work with others will be evaluated.

How to Answer

Provide an example that highlights your teamwork skills, communication, and how you contributed to the team’s success.

Example

“I worked on a cross-functional team to develop a new data analytics platform. I facilitated regular stand-up meetings to ensure everyone was aligned and encouraged open communication, which helped us identify and resolve issues quickly, leading to a successful launch.”

4. Tell us about a time you had to learn a new technology quickly. How did you approach it?

This question assesses your adaptability and willingness to learn.

How to Answer

Share a specific instance where you had to learn a new technology, detailing your learning process and the outcome.

Example

“When I needed to learn Google Cloud Dataflow for a project, I dedicated time to online courses and hands-on practice. I also reached out to colleagues who had experience with the tool for guidance, which helped me ramp up quickly and successfully implement the solution.”

5. How do you handle feedback and criticism?

Your ability to accept and act on feedback is important in a collaborative environment.

How to Answer

Discuss your perspective on feedback and provide an example of how you have used it to improve your work.

Example

“I view feedback as an opportunity for growth. In a previous role, I received constructive criticism on my data visualization skills. I took a course to enhance my abilities and actively sought feedback on my progress, which ultimately improved the quality of my work.”