Key Responsibilities 1. Clinical Data Platform Leadership
Lead the engineering strategy and execution for Clinical Data Platforms supporting Clinical Operations, Data Management, Biostatistics, Medical Affairs, and Regulatory functions.
Drive modernization of enterprise clinical data ecosystems using cloud-native architectures and Data Product principles.
Establish reusable clinical data services, ingestion frameworks, and standardized data models.
Partner with Clinical Development stakeholders to define technology roadmaps and prioritize platform investments.
Ensure scalability, performance, data quality, security, and operational excellence of clinical data solutions.
Data Engineering & Data Products
Lead the design and implementation of enterprise-scale Clinical Data Lakehouse solutions using Databricks and up-to-date cloud technologies.
Build and optimize ETL/ELT pipelines integrating diverse data sources, including:
Clinical Trial Management Systems (CTMS)
Electronic Data Capture (EDC)
ePRO / eCOA platforms
Safety & Pharmacovigilance systems
Regulatory data sources
Real-World Data (RWD)
Medical Affairs data platforms
Develop reusable clinical data products supporting analytics, reporting, AI, and self-service consumption.
Drive best practices for:
Data governance
Metadata management
Data lineage
Data quality
Data interoperability
Artificial Intelligence & Generative AI
Lead implementation of AI-powered solutions to improve clinical trial efficiency, data review, patient insights, and operational decision-making.
Develop and operationalize:
Machine Learning solutions
Predictive Analytics
Generative AI applications
Agentic AI platforms
Clinical Copilots
Intelligent Automation solutions
Retrieval-Augmented Generation (RAG) architectures
Establish AI governance frameworks aligned with Responsible AI principles and regulatory expectations.
Partner with Data Scientists and Product Teams to operationa