Zelis Healthcare Data Engineer Interview Questions + Guide in 2025

Zelis Healthcare is a leading technology-driven company that modernizes the healthcare financial experience, connecting payers, providers, and consumers to enhance the affordability and transparency of care.

As a Data Engineer at Zelis, you will play a crucial role in developing and maintaining data architectures that support the company's mission of optimizing healthcare financial processes. This role involves designing high-level technical solutions for both streaming and batch processing systems, implementing data models aligned with warehouse dimensional standards, and ensuring data quality through rigorous management practices. You will work extensively with the Snowflake Data Platform and utilize programming skills in Python, along with a solid understanding of ETL tools and cloud technologies such as Azure and AWS.

Successful candidates will demonstrate strong analytical skills, a proactive problem-solving approach, and the ability to collaborate with cross-functional teams. They should be comfortable working with large datasets, have experience in data governance, and possess the independence to manage multiple tasks in a fast-paced environment. A commitment to diversity, equity, and inclusion is essential, as Zelis values a workplace that embraces diverse perspectives.

This guide will help you prepare effectively for your interview by providing insights into the skills and attributes that are most relevant to the Data Engineer role at Zelis, allowing you to present yourself as a strong candidate.

The interview process for a Data Engineer at Zelis Healthcare is structured to assess both technical skills and cultural fit within the organization. Candidates can expect a multi-step process that includes several rounds of interviews, each designed to evaluate different competencies and experiences relevant to the role.

1. Initial Phone Screen

The process typically begins with an initial phone screen conducted by a recruiter. This conversation lasts about 30-45 minutes and focuses on understanding the candidate's background, skills, and motivations for applying to Zelis. The recruiter will also provide insights into the company culture and the specifics of the Data Engineer role.

2. Technical Phone Interview

Following the initial screen, candidates will participate in a technical phone interview. This round is usually conducted by a senior data engineer or a technical lead. The focus here is on assessing the candidate's technical expertise, particularly in areas such as Snowflake, Python, and data warehousing concepts. Candidates should be prepared to discuss their previous projects and may be asked to solve technical problems or answer scenario-based questions.

3. Onsite Interviews

Candidates who successfully pass the technical phone interview will be invited for onsite interviews, which may also be conducted virtually. This stage typically consists of multiple rounds, often including interviews with team members, project managers, and possibly upper management. Each interview lasts approximately 45 minutes to an hour and covers a mix of technical and behavioral questions. Candidates should be ready to demonstrate their problem-solving skills, discuss their experience with data management, and explain how they have collaborated with cross-functional teams in the past.

4. Final Interview with Leadership

The final step in the interview process is usually a meeting with leadership or senior management. This interview focuses on assessing the candidate's alignment with Zelis's values and long-term vision. Candidates may be asked about their approach to leadership, mentoring, and how they would contribute to the company's goals in the healthcare sector.

Throughout the interview process, candidates should be prepared to discuss their experiences in data engineering, particularly in relation to healthcare data management, and how they can contribute to the ongoing projects at Zelis.

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

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

Understand the Interview Structure

Zelis Healthcare's interview process can be extensive, often involving multiple rounds, including phone interviews with HR, hiring managers, and team members, followed by onsite interviews. Familiarize yourself with this structure and prepare accordingly. Be ready to discuss your experience in detail, as interviewers may ask specific questions related to your resume and past projects.

Be Prepared for Technical Depth

Given the technical nature of the Data Engineer role, you should be well-versed in Snowflake, Python, and data warehousing concepts. Expect to answer questions that assess your understanding of data modeling, ETL processes, and cloud technologies. Brush up on your knowledge of SQL, particularly in the context of performance optimization and complex queries. Demonstrating a solid grasp of these topics will help you stand out.

Showcase Your Problem-Solving Skills

Zelis values candidates who can anticipate and solve data management issues. Be prepared to discuss specific examples from your past work where you identified problems, implemented solutions, and improved data quality. Use the STAR (Situation, Task, Action, Result) method to structure your responses, as this will help you convey your thought process clearly.

Communicate Your Experience in Healthcare

Since Zelis operates within the healthcare sector, having a background or understanding of healthcare data management can be beneficial. Be ready to discuss any relevant experience you have in this domain, including how you’ve handled sensitive data or collaborated with healthcare stakeholders. This will demonstrate your ability to align with the company’s mission and values.

Emphasize Collaboration and Leadership

The role involves mentoring offshore data engineers and collaborating with product management and engineering teams. Highlight your experience in leading projects, mentoring others, and working cross-functionally. Share examples that illustrate your ability to foster teamwork and drive projects to completion.

Prepare Questions for Your Interviewers

Interviews are a two-way street. Prepare thoughtful questions that show your interest in the role and the company. Inquire about the team dynamics, the technologies they are currently exploring, or how they measure success in the Data Engineering team. This not only demonstrates your enthusiasm but also helps you assess if Zelis is the right fit for you.

Be Aware of Company Culture

Zelis promotes a culture of diversity, equity, inclusion, and belonging. Familiarize yourself with their values and be prepared to discuss how you can contribute to this culture. Share your experiences that reflect your commitment to these principles, as this will resonate well with the interviewers.

Follow Up After the Interview

After your interview, send a 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 your discussion that reinforces your fit for the role. This small gesture can leave a positive impression and keep you top of mind.

By following these tips, you can approach your interview with confidence and clarity, positioning yourself as a strong candidate for the Data Engineer role at Zelis Healthcare. Good luck!

In this section, we’ll review the various interview questions that might be asked during a Data Engineer interview at Zelis Healthcare. The interview process will likely focus on your technical expertise, problem-solving abilities, and experience in data management, particularly with Snowflake and related technologies. Be prepared to discuss your past projects, your approach to data architecture, and how you collaborate with cross-functional teams.

Technical Skills

1. Can you explain your experience with the Snowflake Data Platform and how you have utilized it in past projects?

Your familiarity with Snowflake is crucial, as it is a key technology for this role.

How to Answer

Discuss specific projects where you implemented Snowflake, focusing on the architecture, data modeling, and any challenges you faced.

Example

“In my previous role, I designed a data warehouse using Snowflake that integrated data from multiple sources. I utilized Snowflake’s features like automatic scaling and data sharing to optimize performance and reduce costs. This project improved our reporting speed by 40%.”

2. Describe your experience with ETL tools such as DBT or Informatica. How have you implemented these in your workflows?

Understanding ETL processes is essential for a Data Engineer.

How to Answer

Highlight specific ETL tools you’ve used, the context of their use, and the outcomes of your implementations.

Example

“I have extensive experience with DBT for transforming data in our data warehouse. I created modular transformation scripts that improved our data pipeline efficiency and reduced processing time by 30%. This allowed our analytics team to access up-to-date data more quickly.”

3. How do you approach data modeling, particularly in a dimensional model context?

Data modeling is a critical skill for this role, especially in healthcare data.

How to Answer

Explain your methodology for designing data models, including any specific frameworks or standards you follow.

Example

“I follow Kimball’s dimensional modeling approach, focusing on star schemas to simplify queries for end-users. In a recent project, I designed a star schema for our patient data that improved query performance and made it easier for analysts to generate reports.”

4. Can you discuss a complex data issue you encountered and how you resolved it?

Problem-solving is a key competency for a Data Engineer.

How to Answer

Provide a specific example of a data issue, your analysis process, and the solution you implemented.

Example

“We faced a significant data quality issue where duplicate records were affecting our reporting accuracy. I conducted a root cause analysis and implemented a deduplication process using SQL scripts, which improved our data integrity and reduced reporting errors by 25%.”

5. What strategies do you use to optimize data ingestion and processing?

Efficiency in data processing is vital for handling large datasets.

How to Answer

Discuss specific techniques or tools you use to enhance data ingestion and processing speed.

Example

“I utilize batch processing for large datasets and stream processing for real-time data. For instance, I implemented Apache Kafka for real-time data ingestion, which allowed us to process incoming data streams with minimal latency, enhancing our analytics capabilities.”

Collaboration and Communication

1. How do you ensure effective communication with cross-functional teams, such as product management and business stakeholders?

Collaboration is essential in a data engineering role.

How to Answer

Describe your approach to communication and how you ensure alignment with stakeholders.

Example

“I prioritize regular check-ins with product managers and business analysts to understand their data needs. I also create documentation and visualizations to communicate complex data concepts clearly, ensuring everyone is on the same page.”

2. Describe a time when you had to mentor or lead a team of data engineers. What was your approach?

Leadership and mentorship are important aspects of the role.

How to Answer

Share your experience in mentoring and how you foster a collaborative environment.

Example

“I led a team of junior data engineers on a project to migrate our data warehouse to Snowflake. I organized weekly knowledge-sharing sessions and encouraged them to take ownership of specific components, which not only built their skills but also improved team morale.”

3. How do you handle feedback and criticism from peers or stakeholders?

Being receptive to feedback is crucial for personal and team growth.

How to Answer

Discuss your mindset towards feedback and how you incorporate it into your work.

Example

“I view feedback as an opportunity for growth. When I receive constructive criticism, I take time to reflect on it and implement changes where necessary. For example, after receiving feedback on my documentation style, I adopted a more structured format that improved clarity for my team.”

4. Can you provide an example of how you have driven a data management project from inception to completion?

Demonstrating project management skills is important for this role.

How to Answer

Outline the project lifecycle, your role, and the impact of the project.

Example

“I led a project to restructure our data architecture to improve data accessibility. I collaborated with stakeholders to gather requirements, designed the new architecture, and oversaw the implementation. This project resulted in a 50% reduction in data retrieval times and significantly improved user satisfaction.”

5. How do you prioritize tasks when managing multiple projects?

Time management is key in a fast-paced environment.

How to Answer

Explain your prioritization strategy and any tools you use to manage your workload.

Example

“I use Agile methodologies to prioritize tasks based on business impact and deadlines. I maintain a Kanban board to visualize my workload, which helps me stay organized and focused on high-priority tasks while remaining flexible to changes.”