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.
2. 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
3. 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