MSD Data Engineer Interview Questions + Guide in 2025

MSD is a global healthcare company that drives innovation to help improve health and well-being around the world.

As a Data Engineer at MSD, you will be responsible for designing, implementing, and maintaining data pipelines and architecture that support the organization's data analytics needs. This role involves working closely with data scientists and analysts to ensure that data is efficiently collected, processed, and made accessible for analysis. Key responsibilities include developing and optimizing ETL processes, ensuring data quality, and managing data storage solutions across various platforms, including cloud environments. You will need to possess strong programming skills, particularly in languages such as Python or Java, and have experience with SQL and data warehousing technologies.

In addition to technical expertise, a great fit for this role will have a problem-solving mindset, the ability to collaborate with diverse teams, and a commitment to continuous learning. Given MSD's focus on innovation and data-driven decision-making, candidates should be prepared to discuss their previous projects and demonstrate their adaptability in a dynamic work environment.

This guide will provide you with tailored insights and potential questions you may encounter during your interview, enhancing your readiness and confidence as you pursue this opportunity at MSD.

The interview process for a Data Engineer at MSD is structured to ensure a thorough evaluation of both technical skills and cultural fit. It typically consists of multiple rounds, each designed to assess different competencies and experiences relevant to the role.

1. Initial Screening

The process begins with an initial screening call, usually conducted by an HR representative. This conversation lasts about 30 minutes and focuses on your background, motivations for applying, and a brief overview of the company and the role. The HR representative will also gauge your alignment with MSD's values and culture, which is a critical aspect of their hiring process.

2. Technical Interview

Following the initial screening, candidates typically participate in a technical interview. This round may involve one or more technical managers and focuses on your previous projects and experiences. Expect questions that assess your knowledge of data engineering concepts, tools, and technologies, such as data pipeline design, cloud solutions, and specific programming languages. You may also be asked to solve problems or discuss hypothetical scenarios related to data management and optimization.

3. Behavioral Assessment

In addition to technical skills, MSD places a strong emphasis on behavioral assessments. This round may include situational questions that explore how you handle challenges, collaborate with teams, and adapt to changing environments. Interviewers will be interested in understanding your thought process and how your personality traits align with the company's culture.

4. Final Interview

The final interview often involves a panel of interviewers, which may include senior management or team members. This round typically includes a mix of technical and behavioral questions, as well as a case study or presentation where you may need to demonstrate your problem-solving skills and technical knowledge. The interviewers will assess not only your technical capabilities but also your communication skills and ability to work within a team.

Throughout the process, candidates are encouraged to engage in open dialogue, as MSD values a conversational approach to interviews. This allows both parties to assess fit and expectations effectively.

As you prepare for your interview, consider the types of questions that may arise in each of these rounds.

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

Embrace the Conversational Atmosphere

The interview process at MSD is known for its positive and open dialogue. Approach your interviews as conversations rather than interrogations. This mindset will help you feel more relaxed and allow your personality to shine through. Be prepared to share your experiences and insights in a way that feels natural and engaging, as interviewers are looking for a holistic understanding of who you are, not just your technical skills.

Prepare for Behavioral and Situational Questions

Expect a significant focus on behavioral and situational questions that assess your adaptability and problem-solving skills. Reflect on your past experiences and be ready to discuss specific projects where you faced challenges, how you navigated team dynamics, and the outcomes of your efforts. Use the STAR (Situation, Task, Action, Result) method to structure your responses, ensuring you provide clear and concise examples that highlight your competencies.

Showcase Your Technical Expertise

Technical questions will be a key component of your interviews, so brush up on relevant technologies and methodologies. Be prepared to discuss your experience with data pipelines, cloud solutions, and specific tools like Apache Spark, SQL, and any other technologies mentioned in the job description. Consider preparing a few case studies from your previous work that demonstrate your technical skills and problem-solving abilities, as these will likely be discussed in detail.

Understand the Company Culture

MSD values well-rounded individuals who align with their company culture. Familiarize yourself with their core values and mission, and think about how your personal values align with theirs. Be ready to articulate why you want to work at MSD specifically and how you can contribute to their goals. This alignment will not only help you stand out as a candidate but also ensure that you are genuinely interested in the role and the company.

Be Ready for a Multi-Round Process

The interview process may involve multiple rounds, including HR, technical assessments, and interviews with managers or team members. Be patient and prepared for a thorough evaluation. Use each round as an opportunity to learn more about the company and the team you would be working with. Ask insightful questions that demonstrate your interest and engagement, and don’t hesitate to follow up after interviews to express your continued interest in the position.

Reflect on Your First 90 Days

During your interviews, you may be asked about your goals and plans for the first three months in the role. Take some time to think about how you would approach your onboarding and what you would prioritize. This shows that you are proactive and have a clear vision for your contributions from day one.

By following these tips and preparing thoroughly, you will position yourself as a strong candidate for the Data Engineer role at MSD. Good luck!

In this section, we’ll review the various interview questions that might be asked during a Data Engineer interview at MSD. The interview process will likely assess both your technical skills and your ability to work collaboratively within a team. Be prepared to discuss your previous projects in detail, as well as your problem-solving approaches and adaptability in various situations.

Technical Skills

1. Can you walk us through a specific project where you had to design and implement a data pipeline from start to finish? What challenges did you encounter, and how did you overcome them?

This question aims to evaluate your hands-on experience with data engineering projects and your problem-solving skills.

How to Answer

Detail the project scope, the technologies used, and the specific challenges faced. Highlight your role in overcoming these challenges and the impact of your solutions.

Example

“In my last role, I designed a data pipeline to aggregate sales data from multiple sources. One challenge was ensuring data quality, which I addressed by implementing validation checks at each stage of the pipeline. This not only improved data accuracy but also reduced processing time by 20%.”

2. What technologies would you use for a multi-cloud solution?

This question assesses your knowledge of cloud technologies and your ability to design scalable solutions.

How to Answer

Discuss the specific cloud platforms you are familiar with and how they can be integrated. Mention any relevant tools or frameworks that facilitate multi-cloud architectures.

Example

“I would leverage AWS for its robust data storage options and Google Cloud for its machine learning capabilities. Using tools like Apache Kafka for data streaming would ensure seamless data flow between the clouds, allowing for a more flexible architecture.”

3. What is Apache Spark, and why would you use it in a data engineering context?

This question tests your understanding of big data technologies and their applications.

How to Answer

Explain what Apache Spark is and its advantages over other data processing frameworks. Provide examples of scenarios where Spark would be beneficial.

Example

“Apache Spark is an open-source distributed computing system that excels in processing large datasets quickly. I would use it for real-time data processing tasks, as its in-memory computation capabilities significantly speed up data analysis compared to traditional batch processing.”

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

This question evaluates your approach to maintaining high data standards.

How to Answer

Discuss the methods and tools you use to monitor and validate data quality throughout the data lifecycle.

Example

“I implement automated data validation checks at various stages of the data pipeline, using tools like Great Expectations. Additionally, I conduct regular audits and encourage team members to report any anomalies they encounter.”

5. Describe a time when you had to optimize a data storage and retrieval process. What strategies did you employ?

This question assesses your problem-solving skills and your ability to improve existing systems.

How to Answer

Provide a specific example of a situation where you identified inefficiencies and the steps you took to optimize the process.

Example

“In a previous project, I noticed that our data retrieval times were slow due to inefficient indexing. I implemented a new indexing strategy and partitioned the data based on usage patterns, which reduced retrieval times by 50%.”

Behavioral Questions

1. Describe a situation where you had to collaborate with a diverse team to achieve a common goal. How did you navigate different perspectives, and what was the outcome?

This question evaluates your teamwork and interpersonal skills.

How to Answer

Share a specific example that highlights your ability to work with diverse teams and how you facilitated collaboration.

Example

“I worked on a project with team members from different departments, each bringing unique perspectives. I organized regular check-ins to ensure everyone’s voice was heard, which led to a more comprehensive solution that satisfied all stakeholders.”

2. What was the biggest challenge you faced in your previous role, and how did you overcome it?

This question assesses your resilience and problem-solving abilities.

How to Answer

Choose a significant challenge and explain the steps you took to address it, focusing on the skills you utilized.

Example

“The biggest challenge I faced was a sudden data breach that compromised our data integrity. I led the response team, implementing immediate security measures and conducting a thorough investigation. This experience taught me the importance of proactive data governance.”

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

This question evaluates your time management and organizational skills.

How to Answer

Discuss your approach to prioritization and any tools or methods you use to stay organized.

Example

“I use a combination of project management tools like Trello and the Eisenhower Matrix to prioritize tasks based on urgency and importance. This helps me focus on high-impact activities while ensuring that deadlines are met.”

4. Can you describe a time when you had to adapt to a significant change in a project?

This question assesses your adaptability and flexibility in a dynamic work environment.

How to Answer

Provide an example of a project change and how you adjusted your approach to accommodate it.

Example

“During a project, we had to switch from a monolithic architecture to a microservices approach mid-development. I quickly adapted by re-evaluating our design and collaborating with the team to ensure a smooth transition, which ultimately improved our deployment speed.”

5. Why do you want to work for MSD, and what do you hope to achieve in this role?

This question gauges your motivation and alignment with the company’s values.

How to Answer

Express your enthusiasm for the company and how your goals align with the role and the organization’s mission.

Example

“I admire MSD’s commitment to innovation in healthcare. I hope to leverage my data engineering skills to contribute to projects that enhance patient outcomes, while also growing my expertise in cloud technologies and big data solutions.”