Principal Data Engineer, Safety Analytics

What you'll do

• Design and maintain production-grade data pipelines and curated datasets to support pharmacovigilance activities and regulatory reporting.
• Enable AI, Machine Learning, and GenAI workflows including feature engineering, RAG patterns, and semantic retrieval for safety analytics.
• Manage the end-to-end data lifecycle on Google Cloud Platform, ensuring data continuity, traceability, and integrity from source to consumption.
• Establish and enforce data quality standards, governance practices, and schema versioning for all safety analytics systems.
• Apply GxP validation expertise to ensure data pipelines and infrastructure meet strict regulatory requirements and audit standards.
• Build and operate APIs and microservices-based architectures to operationalize safety analytics and machine learning capabilities.
• Manage cloud infrastructure using Terraform and maintain CI/CD pipelines to optimize performance and cost efficiency.
• Serve as a technical authority by mentoring team members and translating complex safety needs into scalable technical solutions.

What we're looking for

• Master’s degree in Computer Science, Engineering, or a related field (or equivalent experience) is required.
• 5+ years of experience in data engineering or analytics engineering with increasing responsibilities are required.
• Proficiency in Python and SQL programming is required.
• Experience designing and operating APIs and microservices-based architectures is required.
• Solid understanding of SDLC, Agile methodologies, and basic project management skills is required.
• Experience building production workloads on Google Cloud Platform (GCP) is preferred.
• Experience provisioning infrastructure using Terraform and building CI/CD pipelines like Jenkins is preferred.
• Experience in pharmaceuticals, life sciences, healthcare, GCP certification, or enabling AI/ML and GenAI workflows is preferred.