Quintilesims Data Engineer Interview Questions + Guide in 2025

Quintilesims is a leading global provider of advanced analytics, technology solutions, and clinical research services to the life sciences industry, dedicated to improving human health through data-driven insights.

As a Data Engineer at Quintilesims, you will play a critical role in designing, developing, and maintaining data systems and pipelines that support various healthcare analytics initiatives. Key responsibilities include analyzing complex business requirements, creating technical specifications, and implementing efficient data solutions using technologies such as Azure Databricks, PySpark, and SQL. You will also focus on ensuring data quality, security, and compliance while collaborating with cross-functional teams to deliver high-quality data products that drive better healthcare outcomes. A successful candidate will possess strong analytical and problem-solving skills, a solid understanding of data architecture, and the ability to thrive in a fast-paced, evolving environment.

This guide aims to help you prepare effectively for your interview by providing tailored insights and common questions that reflect Quintilesims' culture and values.

The interview process usually depends on the role and seniority. However, you can expect the following on an IQVIA data engineer interview:

Recruiter/Hiring Manager Call Screening

If your CV is among the shortlisted few, a recruiter from the IQVIA Talent Acquisition Team will contact you and verify key details like your experiences and skill level. Behavioral questions may also be part of the screening process.

Sometimes, the data engineer hiring manager stays present during the screening round to answer your queries about the role and the company itself. They may also indulge in surface-level technical and behavioral discussions.

The whole recruiter call should take about 20-30 minutes.

Technical Virtual Interview

Successfully navigating the recruiter round will invite you to the technical screening round. Technical screening for the IQVIA data engineer role is usually conducted through virtual means, including video conference and screen sharing. Questions in this one-hour interview stage may revolve around data systems, ETL pipelines, and SQL queries.

Sometimes, a live coding session focused on MLOps, Python, or SQL might be incorporated. During the round, your proficiency against data engineering fundamentals such as data modeling, data task orchestration, and cloud storage interactions may also be assessed.

Apart from these, ensure you are comfortable with topics like Airflow, CRON jobs, dependency mapping, and familiarity with cloud computing technologies (e.g., GCP).

Onsite Interview Rounds

After a second recruiter call outlining the next stage, you’ll be invited to attend the on-site interview loop. During your day at the IQVIA office, multiple interview rounds, varying with the role, will be conducted. Throughout these interviews, your technical prowess, including programming and data engineering capabilities, will be evaluated against the finalized candidates.

If you were assigned take-home exercises, you may also be invited to a presentation round during the on-site interview for the data engineer role at IQVIA.

Typically, interviews at IQVIA vary by role and team, but commonly Data Engineer interviews follow a fairly standardized process across these question topics.

1. Why are job applications decreasing despite stable job postings?

You observe that the number of job postings per day has remained stable, but the number of applicants has been decreasing. What could be causing this trend?

2. What would you do if friend requests on Facebook are down 10%?

A product manager at Facebook informs you that friend requests have decreased by 10%. How would you address this issue?

3. How would you assess the validity of an AB test result with a 0.04 p-value?

Your company is running an AB test to increase conversion rates on a landing page. The PM finds a p-value of 0.04. How would you evaluate the validity of this result?

4. How would you analyze the performance of a new LinkedIn feature without an AB test?

LinkedIn has launched a feature allowing candidates to message hiring managers directly during the interview process. Due to engineering constraints, an AB test wasn’t possible. How would you analyze the feature’s performance?

5. Should Square hire a customer success manager or offer a free trial for a new product?

Square’s CEO wants to hire a customer success manager for a new software product, while another executive suggests offering a free trial instead. What would be your recommendation?

6. Develop a function str_map to determine if a one-to-one correspondence exists between characters of two strings at the same positions.

Given two strings, string1, and string2, write a function str_map to determine if there exists a one-to-one correspondence (bijection) between the characters of string1 and string2.

7. Build a logistic regression model from scratch using gradient descent and log-likelihood as the loss function.

Create a logistic regression model from scratch without an intercept term. Use basic gradient descent (with Newton’s method) for optimization and the log-likelihood as the loss function. Do not include a penalty term. You may use numpy and pandas but not scikit-learn. Return the parameters of the regression.

8. How would you build a fraud detection model using a dataset of 600,000 credit card transactions?

Imagine you work at a major credit card company and are given a dataset of 600,000 credit card transactions. Describe your approach to building a fraud detection model.

9. How would you interpret coefficients of logistic regression for categorical and boolean variables?

Explain how to interpret the coefficients of logistic regression when dealing with categorical and boolean variables.

10. How would you tackle multicollinearity in multiple linear regression?

Describe the methods you would use to address multicollinearity in a multiple linear regression model.

11. How would you design a facial recognition system for employee clock-in and secure access?

You work as an ML engineer for a large company that wants to implement a facial recognition system for employee clock-in, clock-out, and access to secure systems. The system should also accommodate temporary contract consultants. How would you design this system?

12. How would you handle data preparation for building a machine learning model using imbalanced data?

Explain the steps you would take to prepare data for building a machine-learning model when dealing with imbalanced data.

13. How would you design a machine learning model to classify major health issues based on health features?

You work as a machine learning engineer for a health insurance company. Design a model that classifies if an individual will undergo major health issues based on a set of health features.

14. What metrics and statistical methods would you use to identify dishonest users in a sports app?

You work for a company with a sports app that tracks running, jogging, and cycling data. Formulate a method to identify users who might be cheating, such as driving a car while claiming to be on a bike ride. Specify the metrics and statistical methods you would analyze.

You should plan to brush up on any technical skills and try as many practice interview questions and mock interviews as possible. A few tips for acing your IQVIA data engineer interview include:

• Practice Problem-Solving: Focus on algorithms, data structures, and SQL queries. Platforms like Interview Query provide practice questions and mock interviews to help you prepare.
• Be Familiar with Tools and Frameworks: Commonly used tools in this role include Airflow, GCP, and various data orchestration frameworks. Brush up on these to give relevant answers during technical rounds.
• Behavioral Preparation: IQVIA values a collaborative work culture. Prepare to answer behavioral questions that align with their core values and showcase your ability to work well within a team.

What is the average salary for a Data Engineer at IQVIA?

According to Glassdoor, Data Engineers at IQVIA earn between $104K to $151K per year, with an average of $125K per year.

What kind of technical skills are required for the Data Engineer position?

To excel in this role, you need strong skills in Python, SQL, and shell scripting. Experience with data task orchestration tools like Airflow, CRON, or Prefect, as well as familiarity with cloud storage solutions like GCS or S3, are highly desirable.

What is the company culture like at IQVIA

IQVIA values innovation, collaboration, and diversity. The engineering team is multinational and focused on pushing boundaries in healthcare marketing analytics. Employees are encouraged to learn, grow, and implement new knowledge quickly.

What can I expect in terms of job responsibilities as a Data Engineer at IQVIA?

Job responsibilities include constructing data pipelines, maintaining and optimizing database schemas, performing ad-hoc data analysis, developing workflows, and documenting data architecture. You will also provide guidance on data best practices and automate long-running processes.

The interview process at IQVIA for the Data Engineer position is a comprehensive journey that will test your technical skills, problem-solving abilities, and cultural fit within the team. While the experiences shared by candidates vary, the overall sentiment highlights the importance of both technical acumen and adaptability to the company’s dynamic environment.

If you are preparing for an interview with IQVIA, make sure to leverage the resources available on Interview Query. We’ve compiled a variety of interview questions that may come up, and offer insights into the interview process for various roles, including technical positions like data engineers. At Interview Query, we empower you to excel in your interview through strategic guidance and valuable resources tailored to IQVIA’s hiring process.

Good luck with your interview!