Cardinal Health Data Engineer Interview Questions + Guide in 2025

Cardinal Health, a leading global healthcare services and products company, plays a pivotal role in enhancing healthcare delivery through innovative solutions and data-driven insights.

In the role of Data Engineer at Cardinal Health, you will be responsible for designing, building, and operationalizing large-scale enterprise data solutions using cloud platforms like Google Cloud Platform (GCP). This position requires a comprehensive understanding of data acquisition, integration, and provisioning, ensuring that raw data is accessible and usable throughout the organization. Key responsibilities include optimizing data pipelines, developing data transformation processes, and ensuring the security and integrity of data systems. The ideal candidate will possess advanced skills in SQL, experience with BI tools such as Tableau and Alteryx, and familiarity with agile methodologies. A collaborative mindset and the ability to communicate complex technical concepts to non-technical stakeholders are essential traits for success in this role.

This guide aims to equip you with the insights needed to excel in your interview, helping you demonstrate how your skills and experiences align with Cardinal Health's mission to drive better healthcare outcomes through effective data engineering solutions.

The interview process for a Data Engineer position at Cardinal Health is structured and thorough, designed to assess both technical skills and cultural fit within the organization. The process typically unfolds in several key stages:

1. Initial Screening

The first step is an initial screening, which usually takes place via a phone call with a recruiter. This conversation lasts about 30 minutes and focuses on your background, experience, and motivations for applying to Cardinal Health. The recruiter will also provide insights into the company culture and the specifics of the Data Engineering role.

2. Technical Assessment

Following the initial screening, candidates may be required to complete a technical assessment. This could involve a written test that evaluates your knowledge of data engineering concepts, SQL proficiency, and possibly some programming tasks. The assessment is designed to gauge your technical capabilities and problem-solving skills in a structured format.

3. Panel Interview

Candidates who pass the technical assessment will typically participate in a panel interview. This stage involves multiple interviewers, including senior data engineers and possibly a hiring manager. The panel will ask questions that cover a range of topics, including your experience with data integration, cloud platforms (especially Google Cloud Platform), and your approach to designing and optimizing data pipelines. This interview may also include behavioral questions to assess how you work in teams and handle challenges.

4. Individual Interviews

After the panel interview, candidates may have one or more individual interviews. These sessions are often more focused on specific technical skills and may include coding exercises or case studies relevant to the role. Interviewers will look for your ability to articulate your thought process and demonstrate your technical expertise in real-world scenarios.

5. Final Interview

The final stage of the interview process may involve a conversation with higher-level management or team leads. This interview is typically more strategic, focusing on your long-term career goals, how you align with Cardinal Health's mission, and your potential contributions to the team. It’s also an opportunity for you to ask questions about the company’s direction and the team’s objectives.

As you prepare for your interviews, it’s essential to be ready for a variety of questions that will test your technical knowledge and problem-solving abilities.

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

Understand the Interview Structure

Be prepared for a formal interview process that may include a written test, group panel discussions, and individual interviews. Familiarize yourself with the types of performance-level questions that may be asked. This will help you manage your time effectively and ensure you can showcase your skills and experience throughout the day.

Showcase Your Technical Expertise

As a Data Engineer, you will be expected to demonstrate your proficiency in SQL, GCP, and data integration tools. Prepare to discuss your experience with complex SQL queries, data modeling, and cloud platforms like BigQuery, Dataflow, and Airflow. Be ready to provide specific examples of how you have designed and optimized data pipelines in previous roles.

Emphasize Problem-Solving Skills

Cardinal Health values innovative solutions to complex problems. During the interview, highlight instances where you have developed technical solutions that align with organizational objectives. Discuss your approach to overcoming challenges and how you have contributed to the success of large-scale implementation programs.

Communicate Effectively

Strong written and verbal communication skills are essential for this role. Practice explaining technical concepts in a way that non-technical stakeholders can understand. Be prepared to discuss how you have collaborated with cross-functional teams and communicated project progress, risks, and solutions to leadership.

Align with Company Culture

Cardinal Health emphasizes diversity, inclusion, and a growth mindset. Reflect on how your values align with the company’s mission and culture. Be ready to discuss how you have contributed to a positive team environment and supported the development of less experienced colleagues.

Prepare for Behavioral Questions

Expect behavioral questions that assess your ability to work on complex projects and your approach to mentoring others. Use the STAR (Situation, Task, Action, Result) method to structure your responses, providing clear examples of your past experiences that demonstrate your capabilities.

Stay Current with Industry Trends

Keep abreast of the latest trends in data engineering, cloud technologies, and analytics. Being knowledgeable about emerging technologies and best practices will not only help you answer questions but also demonstrate your commitment to continuous learning and improvement.

Follow Up Thoughtfully

After the interview, send a personalized thank-you note to your interviewers. Express your appreciation for the opportunity to interview and reiterate your enthusiasm for the role. This small gesture can leave a positive impression and reinforce your interest in joining the team.

By following these tips, you will be well-prepared to showcase your skills and fit for the Data Engineer role at Cardinal Health. Good luck!

In this section, we’ll review the various interview questions that might be asked during a Data Engineer interview at Cardinal Health. The interview process is likely to be formal and may include a written test, group panel discussions, and individual interviews. Candidates should be prepared to demonstrate their technical expertise, problem-solving abilities, and understanding of data engineering principles.

Technical Skills

1. Can you explain the process of designing and implementing a data pipeline on GCP?

This question assesses your understanding of data pipeline architecture and your hands-on experience with GCP tools.

How to Answer

Discuss the steps involved in designing a data pipeline, including data ingestion, transformation, and storage. Mention specific GCP services you would use, such as Dataflow or BigQuery.

Example

“I would start by identifying the data sources and the required transformations. Using GCP Dataflow, I would create a pipeline to ingest data, apply necessary transformations, and then store the results in BigQuery for analysis. This approach ensures scalability and efficiency in handling large datasets.”

2. What are the key differences between Dataflow and Dataproc?

This question tests your knowledge of GCP services and their appropriate use cases.

How to Answer

Explain the primary functions of each service and when to use one over the other, focusing on batch vs. stream processing.

Example

“Dataflow is designed for stream and batch processing, making it ideal for real-time analytics. In contrast, Dataproc is a managed Spark and Hadoop service, which is better suited for batch processing and big data workloads. I would choose Dataflow for real-time data ingestion and Dataproc for large-scale batch processing tasks.”

3. Describe your experience with SQL and how you optimize complex queries.

This question evaluates your SQL skills and your ability to enhance performance.

How to Answer

Share your experience with writing SQL queries and specific techniques you use to optimize them, such as indexing or query restructuring.

Example

“I have extensive experience writing complex SQL queries for data extraction and reporting. To optimize performance, I often use indexing on frequently queried columns and analyze query execution plans to identify bottlenecks. This approach has significantly reduced query execution times in my previous projects.”

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

This question focuses on your approach to maintaining high data quality standards.

How to Answer

Discuss the methods you use to validate data, such as automated testing, data profiling, and monitoring.

Example

“I implement data validation checks at various stages of the data pipeline to ensure data quality. This includes automated tests to check for anomalies and data profiling to assess data completeness and accuracy. Regular monitoring also helps in identifying and addressing data quality issues proactively.”

5. Can you explain a challenging data engineering problem you faced and how you resolved it?

This question assesses your problem-solving skills and ability to handle complex situations.

How to Answer

Describe a specific challenge, the steps you took to resolve it, and the outcome.

Example

“In a previous project, I encountered performance issues with a data pipeline that processed large volumes of data. I analyzed the pipeline and identified that the bottleneck was in the data transformation stage. By refactoring the transformation logic and leveraging GCP’s Dataflow for parallel processing, I improved the pipeline’s performance by 50%.”

Data Modeling and Architecture

1. What are the best practices for designing a data model in a cloud environment?

This question evaluates your understanding of data modeling principles in cloud architectures.

How to Answer

Discuss key considerations such as normalization, denormalization, and the use of cloud-native data stores.

Example

“When designing a data model in a cloud environment, I focus on balancing normalization for data integrity and denormalization for query performance. I also leverage cloud-native data stores like BigQuery, which allows for flexible schema design and efficient querying capabilities.”

2. How do you approach data governance and security in your data engineering projects?

This question assesses your awareness of data governance practices and security measures.

How to Answer

Explain your strategies for ensuring data governance and security, including compliance with regulations.

Example

“I prioritize data governance by implementing access controls and data classification policies. I also ensure compliance with regulations like GDPR by anonymizing sensitive data and regularly auditing data access logs to prevent unauthorized access.”

3. Describe your experience with ETL processes and tools.

This question evaluates your familiarity with ETL methodologies and tools.

How to Answer

Share your experience with ETL processes, the tools you’ve used, and any challenges you faced.

Example

“I have extensive experience with ETL processes, primarily using tools like Apache Airflow for orchestration and Talend for data integration. One challenge I faced was managing dependencies between tasks, which I resolved by implementing a clear task scheduling strategy in Airflow to ensure smooth execution.”

4. What strategies do you use for data ingestion from various sources?

This question assesses your knowledge of data ingestion techniques and tools.

How to Answer

Discuss the different methods you use for data ingestion, including batch and real-time approaches.

Example

“I utilize both batch and real-time data ingestion strategies depending on the use case. For batch ingestion, I often use GCP’s Cloud Storage to stage data before processing. For real-time ingestion, I leverage Pub/Sub to stream data directly into Dataflow for immediate processing.”

5. How do you handle schema changes in a data warehouse?

This question evaluates your approach to managing schema evolution.

How to Answer

Explain your strategies for handling schema changes without disrupting existing processes.

Example

“I handle schema changes by implementing versioning in the data model and using techniques like backward compatibility. This allows me to introduce new fields or modify existing ones without breaking existing queries or reports. Additionally, I communicate changes to stakeholders to ensure alignment.”

Collaboration and Communication

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

This question assesses your communication skills and ability to bridge the gap between technical and non-technical teams.

How to Answer

Discuss your approach to simplifying complex concepts and using visual aids.

Example

“I focus on using simple language and analogies to explain technical concepts to non-technical stakeholders. I also use visual aids like diagrams and dashboards to illustrate data flows and insights, making it easier for them to understand the impact of our work.”

2. Describe a time when you had to collaborate with cross-functional teams.

This question evaluates your teamwork and collaboration skills.

How to Answer

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

Example

“In a recent project, I collaborated with the analytics and business teams to develop a new reporting solution. By holding regular meetings and gathering feedback from all stakeholders, we were able to create a solution that met everyone’s needs and improved decision-making across the organization.”

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

This question assesses your time management and prioritization skills.

How to Answer

Explain your approach to prioritizing tasks based on urgency and impact.

Example

“I prioritize tasks by assessing their urgency and impact on the overall project goals. I use project management tools to track progress and communicate with my team to ensure alignment on priorities. This approach helps me stay focused and deliver high-quality results on time.”

4. How do you handle conflicts within a team?

This question evaluates your conflict resolution skills.

How to Answer

Discuss your approach to addressing conflicts and fostering a collaborative environment.

Example

“When conflicts arise, I address them directly by facilitating open discussions between the parties involved. I encourage everyone to share their perspectives and work towards a mutually beneficial solution. This approach not only resolves the conflict but also strengthens team dynamics.”

5. Can you provide an example of how you mentored a junior team member?

This question assesses your leadership and mentoring abilities.

How to Answer

Share a specific instance where you provided guidance and support to a junior colleague.

Example

“I mentored a junior data engineer by providing regular one-on-one sessions to discuss their projects and challenges. I shared best practices and resources to help them improve their skills. Over time, I saw significant growth in their confidence and technical abilities, which positively impacted our team’s performance.”