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MSDData Engineer
Updated · Reviewed by the Dataford team

MSD Data Engineer interview questions & guide 2026

Every question MSD interviewers actually ask, the frameworks that win the room, and the language hiring managers respond to.

3 rounds · ≈ 3-5 weeks
1
HR Screening Call
2
Technical Assessment
3
Core Interview Rounds

What is a Data Engineer at MSD?

As a Data Engineer at MSD, you will play a pivotal role in bridging the gap between raw healthcare data and life-saving scientific breakthroughs. MSD relies heavily on data-driven decision-making to accelerate drug discovery, optimize clinical trials, streamline global supply chains, and enhance commercial operations. Your work will directly impact how researchers, data scientists, and business leaders access and utilize critical datasets, making your role highly strategic and influential.

The data ecosystem at MSD is exceptionally complex and operates at a massive scale. You will be responsible for designing, building, and maintaining robust data pipelines that ingest structured and unstructured data from diverse sources, such as clinical trials, genomic sequencing, and global manufacturing systems. By ensuring the reliability, quality, and accessibility of this data, you enable advanced analytics and machine learning models that can shorten the time it takes to bring new therapies to patients who need them.

This position offers a unique blend of technical challenge and meaningful purpose. You will work with modern cloud architectures, cutting-edge big data technologies, and collaborative cross-functional teams. Succeeding in this role requires not only strong technical capabilities in data pipelining and database design but also a deep appreciation for data governance, security, and the ethical implications of managing sensitive health information.

Common Interview Questions

The following questions are compiled from real interview experiences of candidates who interviewed for the Data Engineer position at MSD. While your specific interview may vary depending on the team and location, these questions represent the core patterns and technical concepts you should expect to encounter.

SQL & Database Design

This category evaluates your ability to write efficient queries, structure database schemas, and optimize data retrieval processes.

  • Write a SQL query to calculate patient adherence metrics over a specific treatment timeline.
  • Explain the difference between clustered and non-clustered indexes and when you would use each.

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03 · Question bank

The questions most likely to come up

Sorted by relevance to this company
Normalization vs Denormalization TradeoffsMedium
Explain normalization, why it improves data integrity, and when denormalization is a practical performance tradeoff.
schema designperformanceData Modeling
ETL vs ELT Trade-offsEasy
Compare ETL and ELT, and explain when ELT is the better pipeline pattern.
ETLELTData Modeling
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Getting Ready for Your Interviews

To succeed in the MSD hiring process, you must prepare holistically, balancing your technical expertise with strong communication and behavioral preparation. Interviewers look for well-rounded professionals who can write clean code, design scalable architectures, and collaborate effectively across global teams.

Role-Related Knowledge – You must demonstrate a deep understanding of core data engineering principles, cloud technologies, and modern data architectures. Be ready to discuss the pros and cons of different tools and explain why you would choose a specific technology for a given problem.

Problem-Solving & Structure – Interviewers care deeply about your thought process. When faced with ambiguous scenario-based questions, do not jump straight to the final solution. Instead, ask clarifying questions, state your assumptions, and outline a structured, step-by-step implementation plan.

Collaboration & Communication – Operating in a global biopharmaceutical company means working with diverse stakeholders. You must be able to articulate your technical decisions clearly and show that you can build strong relationships with product managers, data scientists, and business leaders.

Mission AlignmentMSD is a purpose-driven organization dedicated to saving and improving lives. Showing genuine enthusiasm for the company's mission and demonstrating how your work as a Data Engineer supports that mission can set you apart from other candidates.

Interview Process Overview

The interview process for a Data Engineer at MSD is designed to be comprehensive, professional, and highly structured. While there may be minor variations depending on the seniority of the role and the geographical location (such as Prague, Hyderabad, or Costa Rica), the overall flow remains consistent and transparent. The company focuses on evaluating both your technical capabilities and your behavioral alignment with their core values.

The journey typically begins with an initial HR screening call, which is straightforward and conversational. This is followed by a technical assessment phase, which may involve an online coding assessment, a written technical questionnaire, or a practical SQL test. Once you pass the screening phases, you will move on to the core interview rounds, which are often grouped into a single-day hiring event or scheduled closely together to keep the process moving efficiently.

Throughout the process, you can expect a highly professional atmosphere. Interviewers are generally described as respectful, knowledgeable, and eager to have a genuine conversation about your experience rather than putting you through an adversarial interrogation.

06 · The loop

The interview process, end to end

≈ 3-5 weeks · 3 rounds
1
HR Screening Call

A straightforward and conversational initial call with HR to assess fit.

2
Technical Assessment

May involve an online coding assessment, a written technical questionnaire, or a practical SQL test.

3
Core Interview Rounds

Multiple interviews often grouped into a single-day hiring event or scheduled closely together.

This visual timeline outlines the typical progression from your initial contact with the recruiter to the final decision. Candidates should use this roadmap to pace their preparation, ensuring they allocate sufficient time to practice coding and SQL early in the process, while saving behavioral and architectural practice for the later rounds.

Deep Dive into Evaluation Areas

Data Pipeline Design & Architecture

Designing scalable, reliable, and maintainable data pipelines is at the heart of the Data Engineer role at MSD. You will be evaluated on your ability to architect data flows that can handle large volumes of diverse data while ensuring data integrity and compliance.

Be ready to go over:

  • ETL/ELT Frameworks – When to transform data in-flight versus transforming it within the target data warehouse.
  • Data Quality & Monitoring – Implementing automated checks, data validation, and alerting mechanisms to detect pipeline failures or data anomalies.

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  • Recent, real interview reports
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08 · Topic breakdown

What they actually test for

Weighting based on 1 reported loops
Topic distribution
All topics
SQLData EngineeringBehavioral Interview / Psychosocial EvaluationStatisticsCommunication Skills

Key Responsibilities

As a Data Engineer at MSD, your day-to-day activities will revolve around building the data foundation that powers the company's scientific and business initiatives. You will work closely with data scientists, clinical researchers, business analysts, and software engineers to understand their data needs and deliver high-quality data solutions.

Your primary responsibilities will include:

  • Designing, constructing, installing, testing, and maintaining highly scalable data management systems and pipelines.
  • Integrating diverse and complex data sources, ensuring that data flows seamlessly across different platforms and systems.
  • Collaborating with data governance and security teams to implement strict data access controls, encryption, and compliance standards.
  • Optimizing data delivery and storage systems to improve performance, reliability, and cost-efficiency.
  • Troubleshooting pipeline failures, resolving data quality issues, and continuously improving data infrastructure.

By executing these responsibilities effectively, you will help MSD unlock the full potential of its data, enabling faster insights, better decision-making, and ultimately, improved patient outcomes.

Role Requirements & Qualifications

To be a competitive candidate for the Data Engineer position at MSD, you should possess a strong blend of technical skills, relevant experience, and interpersonal capabilities.

Technical Skills

  • Must-have skills – Proficiency in SQL and at least one programming language (such as Python, Scala, or Java). Strong experience with cloud platforms (AWS or Azure) and big data technologies (like Spark, Hadoop, or Databricks). Solid understanding of data warehousing concepts and ETL/ELT pipeline development.
  • Nice-to-have skills – Experience working with orchestration tools (such as Airflow or Prefect), containerization (Docker, Kubernetes), and infrastructure as code (Terraform). Familiarity with data governance tools and practices.

Experience & Education

  • A bachelor's or master's degree in Computer Science, Information Technology, Data Engineering, or a related quantitative field.
  • Proven experience working as a data engineer, ideally in a large-scale enterprise environment.
  • Experience in the healthcare, pharmaceutical, or biotechnology sector is highly advantageous but not strictly mandatory.

Soft Skills

  • Strong analytical and problem-solving abilities.
  • Excellent communication skills, with the ability to explain technical concepts to diverse audiences.
  • A collaborative mindset and the ability to work effectively in global, cross-functional teams.

Frequently Asked Questions

Q: How difficult is the Data Engineer interview at MSD? A: Candidates generally describe the interview process as "average" in difficulty. The questions are straightforward and focus heavily on real-world application, practical SQL skills, and systematic problem-solving rather than highly theoretical or abstract competitive programming puzzles.

Q: What is the typical timeline for the hiring process? A: The process is designed to be efficient. After the initial HR screen and technical assessment, the core interviews are often completed in a single day or over a couple of weeks. However, the time from the final interview to an official offer can vary, sometimes taking a few weeks due to internal approvals.

Q: How important is domain knowledge in healthcare or pharma? A: While prior experience in healthcare or pharma is a strong plus, it is not a strict requirement. MSD values strong core data engineering skills and a willingness to learn the domain. Demonstrating an understanding of data compliance (like HIPAA or GDPR) is highly beneficial.

Q: What technologies does MSD primarily use for data engineering? A: MSD utilizes a modern, cloud-first technology stack. You can expect to work extensively with AWS or Azure, Databricks, Apache Spark, Python, SQL, and various modern data warehousing and orchestration tools.

Q: Does MSD support remote or hybrid work for Data Engineers? A: MSD generally offers a flexible, hybrid work model, allowing engineers to balance working from home with collaborating in person at their state-of-the-art hubs in locations like Prague, Hyderabad, and Costa Rica. Specific arrangements depend on the team and location.

Other General Tips

Master the "Where to Start" Framework: When asked situational questions, always begin by defining the scope. Clarify the business goals, identify the data sources, outline the ingestion strategy, describe the transformation logic, and explain how the data will be stored and consumed. This structured approach showcases your maturity as an engineer.

Brush Up on Statistics: Even as a data engineer, having a solid grasp of basic statistical concepts can be a major differentiator, especially when interviewing for teams that support clinical trials or advanced R&D.

Be Ready for Conversational Technical Rounds: Many candidates report that the technical interviews feel more like a peer-to-peer technical discussion than an exam. Approach the interview as a collaborative session where you and the interviewer are working together to solve a practical data problem.

Summary & Next Steps

The Data Engineer role at MSD is an exceptional opportunity to apply your technical skills to work that truly matters. By building the data pipelines and architectures that power global health research, clinical trials, and manufacturing, you will be a vital contributor to a company that impacts millions of lives daily. The interview process is designed to find well-rounded, collaborative, and technically sound professionals who are excited about this mission.

To maximize your chances of success, focus your preparation on solidifying your SQL fundamentals, practicing structured system design, and preparing compelling stories that highlight your teamwork and problem-solving abilities. Approach the interviews with confidence, professional curiosity, and a genuine enthusiasm for the impactful work being done at MSD.

For more detailed candidate insights, interview reviews, and tailored preparation resources, explore the comprehensive datasets available on Dataford.

This compensation overview reflects the competitive salary structures MSD offers to attract top-tier engineering talent globally. When evaluating your potential offer, consider the complete package, which typically includes performance bonuses, health benefits, and robust opportunities for professional growth and international collaboration.

16 · FAQ

MSD Data Engineer interview FAQ

Answered from real candidate and compensation data
How hard are MSD Data Engineer interviews, and what offer rate do candidates report?
Candidates who interviewed for the MSD Data Engineer role most often reported the difficulty as average. Across reported interviews, the offer rate is 9%.
What is the MSD Data Engineer interview process like, and how many stages does it include?
The process starts with an HR screening call that is described as straightforward and conversational. After that, candidates take a technical assessment, which may be an online coding assessment, a written technical questionnaire, or a practical SQL test. The core interview rounds then happen either as multiple interviews grouped into a single-day hiring event or scheduled closely together.
What topics does MSD test for the Data Engineer role?
SQL and Data Engineering are core topics, and the list also includes Statistics, Problem Solving, and Communication Skills. You should expect Behavioral Interview or Psychosocial Evaluation, and there is an emphasis on project-based technical questions and technical interviewing.
What should I prioritize when preparing SQL and database design for MSD Data Engineer interviews?
Be ready to write efficient SQL queries and explain database design choices. Typical areas include indexing concepts like clustered versus non-clustered indexes, schema design for multi-center clinical trial tracking, and performance work like optimizing slow queries with multiple large joins. You may also be asked when denormalization is preferred over normalization.
What kinds of data pipeline and ETL/ELT questions should I expect at MSD for Data Engineer?
Expect scenario-based pipeline questions that test how you start from ambiguity and turn requirements into steps. Topics include building an ETL pipeline for daily data from multiple vendors, migrating a legacy on-prem data warehouse to the cloud, handling data quality issues like missing values and schema drift, and designing processing for real-time streaming data from medical wearable devices. You should also be able to discuss factors for choosing between ETL and ELT architectures.
What pay range do candidates report for MSD Data Engineer, and does it vary?
This role interview prep summary includes candidate-reported pay inputs, but it does not list specific dollar amounts for MSD Data Engineer compensation. The only supported pay-related detail here is that pay varies by level and location, so you should confirm the exact range in the job posting or recruiter screen.