To excel in the Pra Health Sciences interview process, you must understand the specific technical and behavioral dimensions upon which you will be graded.
Clinical Data Engineering & SAS Programming
For roles aligned with clinical data processing, your technical review will focus heavily on your ability to manipulate, structure, and validate clinical data in accordance with global standards.
Be ready to go over:
- CDISC Standards – Deep knowledge of SDTM and ADaM implementation guidelines, metadata structure, and controlled terminology.
- SAS Programming – Proficiency in the SAS macro facility, data step processing, SQL procedure, and generating standardized TFLs.
- Dataset Validation – Methods for validating datasets, programming independently to compare results (double-programming), and identifying discrepancies.
Advanced concepts (less common):
- Developing custom XML schemas for Define.xml submissions.
- Integrating external API data feeds directly into clinical data repositories.
Example questions or scenarios:
- "Explain how you would programmatically handle a situation where a patient's treatment start date is recorded as occurring before their randomization date."
- "Describe the process of converting raw electronic data capture (EDC) tables into SDTM-compliant domains."
Enterprise Web Development (.NET & SQL)
For platform and product engineering roles, you will be evaluated on your ability to build secure, high-performance, and scalable web services that manage sensitive data.
Be ready to go over:
- Backend Architecture – Designing RESTful services using .NET Core, understanding middleware, dependency injection, and asynchronous programming.
- Database Management – Writing complex SQL queries, indexing strategies, transaction management, and ensuring database security.
- API Security – Implementing robust authentication and authorization protocols (OAuth2, JWT) to protect patient health information (PHI).
Advanced concepts (less common):
- Designing event-driven architectures using message brokers like RabbitMQ or Kafka.
- Implementing containerized deployments using Docker and Kubernetes.
Example questions or scenarios:
- "How would you refactor a legacy monolithic database query into a set of optimized, decoupled microservices?"
- "Explain how you would handle database locking and concurrency issues when multiple users are updating clinical trial records simultaneously."
Behavioral & Situational Fit
Every candidate is evaluated on their teamwork, communication, and alignment with the rigorous, quality-first culture of Pra Health Sciences.
Be ready to go over:
- Conflict Resolution – Navigating technical disagreements within an engineering or cross-functional team.
- Time Management – Balancing daily engineering tasks with urgent, unplanned requests from study teams.
- Client Management – Communicating technical limitations or delivery delays to non-technical stakeholders or clients.
Advanced concepts (less common):
- Mentoring junior programmers and establishing coding standards across a distributed team.
- Driving process improvements to reduce software development lifecycle (SDLC) bottlenecks.
Example questions or scenarios:
- "Tell me about a time when you had to explain a highly technical data issue to a clinical trial manager who had no programming background."
- "Describe a situation where a client requested a feature that violated data compliance standards. How did you handle the request?"