MultiPlan Data Engineer Interview Questions + Guide in 2025

MultiPlan is committed to transforming the healthcare landscape by leveraging innovative data solutions to bend the cost curve for all stakeholders.

As a Data Engineer at MultiPlan, you will play a pivotal role in designing and implementing enterprise data architecture, strategy, and integration. This position involves developing scalable data pipelines, managing data warehouses, and ensuring data quality while collaborating across various teams to meet evolving business needs. You will be expected to utilize your expertise in SQL, cloud technologies (such as Oracle Cloud Infrastructure and Snowflake), and data integration methodologies (like API and Kafka) to drive data-driven decision-making within the organization. The ideal candidate will have a background in healthcare data environments, strong analytical skills, and a commitment to fostering an innovative and accountable work culture that aligns with MultiPlan's values.

This guide is designed to equip you with the insights and knowledge necessary to excel in your interview for the Data Engineer role at MultiPlan, thereby enhancing your chances of success.

The interview process for a Data Engineer at MultiPlan is structured to assess both technical and interpersonal skills, ensuring candidates align with the company's innovative and collaborative culture. The process typically consists of several rounds, each designed to evaluate different competencies relevant to the role.

1. Initial Recruiter Call

The first step is a phone interview with a recruiter, lasting about 30 minutes. This conversation focuses on your background, experience, and motivation for applying to MultiPlan. The recruiter will also provide insights into the company culture and the specifics of the Data Engineer role, assessing your fit within the organization.

2. Hiring Manager Interview

Following the initial call, candidates will have a second interview with the hiring manager. This session dives deeper into your technical skills and experience, particularly in data architecture, SQL, and cloud technologies. Expect questions that explore your past projects and how they relate to the responsibilities outlined in the job description.

3. Technical Interview

The third round typically involves a technical interview, which may be conducted by a senior data engineer or a member of the data architecture team. This interview focuses on your proficiency in data engineering concepts, including data modeling, ETL processes, and integration methodologies. You may be asked to solve technical problems or discuss your approach to building data pipelines and managing data quality.

4. Panel Interview

The final round is often a panel interview with multiple team members, including data scientists and other engineers. This session assesses your ability to collaborate and communicate effectively across disciplines. Expect a mix of behavioral questions and case studies that require you to demonstrate your problem-solving skills and your understanding of data governance and compliance, particularly in a healthcare context.

Throughout the process, candidates should be prepared to discuss their experience with specific technologies such as Python, Java, Snowflake, and cloud platforms like Oracle Cloud Infrastructure.

As you prepare for your interviews, consider the types of questions that may arise in each round, focusing on both your technical expertise and your ability to work within a team-oriented environment.

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

Understand the Company’s Mission and Values

Before your interview, familiarize yourself with MultiPlan's mission to "bend the cost curve in healthcare." This understanding will not only help you answer questions about why you want to work there but also allow you to align your responses with the company's values of innovation, accountability, and diversity. Be prepared to discuss how your personal values and experiences resonate with their mission.

Prepare for a Multi-Round Interview Process

Expect a structured interview process that may include multiple rounds, such as a recruiter call, a technical interview, and a panel interview. Each round may focus on different aspects of your skills and experiences. Be ready to articulate your past work experiences, particularly those that demonstrate your technical expertise and problem-solving abilities. Practice discussing your previous roles in detail, as interviewers often focus on your work history.

Showcase Your Technical Skills

Given the emphasis on SQL, algorithms, and data engineering, ensure you are well-prepared to discuss your technical skills. Brush up on SQL queries, data modeling, and integration methodologies like APIs and Kafka. Be ready to solve technical problems on the spot, as interviewers may ask you to demonstrate your thought process and approach to data challenges.

Be Ready for Behavioral Questions

Expect behavioral questions that assess your teamwork, leadership, and problem-solving skills. Use the STAR (Situation, Task, Action, Result) method to structure your responses. Prepare specific examples from your past experiences that highlight your ability to collaborate with cross-functional teams and drive data-driven decisions.

Emphasize Your Experience with Data Governance and Quality

Given the importance of data governance and quality in the role, be prepared to discuss your experience in these areas. Highlight any past projects where you implemented data quality measures or worked with data governance teams. This will demonstrate your understanding of the critical nature of data integrity in healthcare.

Communicate Clearly and Confidently

Effective communication is key in this role, as you will need to collaborate with various stakeholders. Practice articulating your thoughts clearly and concisely. Be prepared to explain complex technical concepts in a way that non-technical stakeholders can understand. This skill will be crucial in ensuring successful collaboration across departments.

Ask Insightful Questions

At the end of your interview, take the opportunity to ask thoughtful questions about the team dynamics, the technologies they use, and the challenges they face. This not only shows your interest in the role but also helps you gauge if the company culture aligns with your expectations. Questions about how the team collaborates on data projects or how they measure success can provide valuable insights.

Follow Up Professionally

After your interview, send a thank-you email to express your appreciation for the opportunity to interview. Reiterate your enthusiasm for the role and briefly mention a key point from your conversation that reinforces your fit for the position. This small gesture can leave a positive impression and keep you top of mind as they make their decision.

By following these tips, you can present yourself as a well-prepared and enthusiastic candidate who is ready to contribute to MultiPlan's mission and success. Good luck!

In this section, we’ll review the various interview questions that might be asked during a Data Engineer interview at MultiPlan. The interview process will likely assess your technical skills, problem-solving abilities, and understanding of data architecture and integration, particularly in the healthcare domain. Be prepared to discuss your previous experiences, technical knowledge, and how you can contribute to the company's mission of optimizing healthcare costs through innovative data solutions.

General Background and Experience

1. Why do you want to work at MultiPlan?

This question aims to gauge your motivation and alignment with the company's mission and values.

How to Answer

Express your enthusiasm for the healthcare industry and how MultiPlan's goals resonate with your professional aspirations. Highlight any specific aspects of the company that attract you.

Example

"I am passionate about leveraging data to improve healthcare outcomes, and I admire MultiPlan's commitment to bending the cost curve in healthcare. I believe my skills in data engineering can contribute to innovative solutions that enhance service delivery and efficiency."

2. Tell us about your previous position.

This question seeks to understand your work history and how it relates to the role you're applying for.

How to Answer

Provide a concise overview of your previous role, focusing on relevant responsibilities and achievements that align with the Data Engineer position.

Example

"In my previous role as a Data Engineer, I was responsible for designing and implementing data pipelines that supported analytics and reporting. I collaborated with cross-functional teams to ensure data integrity and optimized performance, which resulted in a 30% reduction in processing time."

Technical Skills and Knowledge

3. What is your experience with SQL and database management?

This question assesses your technical proficiency in SQL and your understanding of database systems.

How to Answer

Discuss your experience with SQL, including specific databases you've worked with, and any relevant projects that demonstrate your skills.

Example

"I have over five years of experience working with SQL, primarily in PostgreSQL and MySQL. I have designed complex queries for data extraction and transformation, and I have also optimized database performance by indexing and restructuring tables."

4. Can you explain the concept of data modeling and its importance?

This question tests your understanding of data modeling principles and their application in data engineering.

How to Answer

Define data modeling and explain its significance in ensuring data quality and usability within an organization.

Example

"Data modeling is the process of creating a visual representation of data structures and relationships. It is crucial because it helps ensure data integrity, facilitates communication among stakeholders, and serves as a blueprint for database design."

5. Describe your experience with cloud data platforms, specifically OCI and Snowflake.

This question evaluates your familiarity with cloud technologies relevant to the role.

How to Answer

Share your experience with cloud platforms, focusing on specific projects or tasks you've completed using OCI or Snowflake.

Example

"I have worked extensively with Snowflake for data warehousing solutions, where I implemented ETL processes to ingest and transform data. Additionally, I have experience with Oracle Cloud Infrastructure, where I managed data storage and processing tasks to support analytics initiatives."

Data Integration and Engineering

6. How do you approach building scalable data pipelines?

This question assesses your understanding of data pipeline architecture and best practices.

How to Answer

Discuss your methodology for designing and implementing data pipelines, including tools and technologies you prefer.

Example

"I start by understanding the data sources and the required transformations. I then use tools like Apache Kafka for real-time data streaming and Apache Airflow for orchestrating workflows. My focus is on ensuring scalability and reliability to handle increasing data volumes."

7. What integration methodologies are you familiar with?

This question tests your knowledge of various data integration techniques.

How to Answer

List the integration methodologies you have experience with and provide examples of how you've applied them in past projects.

Example

"I am familiar with several integration methodologies, including API-based integrations, ETL processes, and event-driven architectures using tools like Apache Nifi and Kafka. For instance, I implemented an API integration that allowed real-time data sharing between our CRM and data warehouse."

8. Can you explain the importance of data governance in data engineering?

This question evaluates your understanding of data governance principles and their relevance to data engineering.

How to Answer

Define data governance and discuss its role in maintaining data quality, security, and compliance.

Example

"Data governance is essential for ensuring data quality, security, and compliance with regulations like HIPAA. It establishes policies and standards for data management, which helps organizations maintain trust in their data and make informed decisions."

Problem-Solving and Analytical Skills

9. Describe a challenging data issue you faced and how you resolved it.

This question assesses your problem-solving skills and ability to handle data-related challenges.

How to Answer

Provide a specific example of a data issue, the steps you took to resolve it, and the outcome.

Example

"I encountered a significant data quality issue where duplicate records were affecting our reporting accuracy. I conducted a thorough analysis to identify the root cause, implemented deduplication processes, and established validation rules to prevent future occurrences, resulting in improved data integrity."

10. How do you ensure data reliability and quality in your work?

This question evaluates your approach to maintaining high data standards.

How to Answer

Discuss the practices and tools you use to monitor and ensure data quality throughout the data lifecycle.

Example

"I implement automated data validation checks and monitoring tools to ensure data quality. Additionally, I conduct regular audits and collaborate with data governance teams to establish best practices for data management."

Collaboration and Communication

11. How do you collaborate with cross-functional teams in your projects?

This question assesses your teamwork and communication skills.

How to Answer

Describe your approach to collaboration, including how you communicate with different stakeholders.

Example

"I prioritize open communication and regular check-ins with cross-functional teams. I use project management tools to track progress and ensure everyone is aligned on goals. This collaborative approach has led to successful project outcomes and stronger team relationships."

12. What role do you believe a Data Engineer plays in a data-driven organization?

This question seeks to understand your perspective on the importance of the Data Engineer role.

How to Answer

Discuss the key responsibilities of a Data Engineer and how they contribute to the organization's success.

Example

"A Data Engineer plays a critical role in enabling data-driven decision-making by building and maintaining the infrastructure that supports data analytics. They ensure that data is accessible, reliable, and of high quality, which empowers teams to derive insights and drive business strategies."