• Architect and implement enterprise-grade data platforms in Azure, supporting structured and unstructured data across clinical and corporate domains. • Design and maintain scalable data pipelines and repositories that support real-time and batch processing. • Ensure data integrity, security, and compliance with GxP and regulatory standards. • Map and optimize end-to-end data flows across clinical operations, including study startup, site management, patient recruitment, and monitoring. • Extend data architecture and analytics capabilities to support Finance, HR, BD, and other internal functions. • Integrate data from leading clinical applications such as Veeva Vault Clinical, CTMS, and EDC systems, as well as ERP, HRIS, and CRM platforms. • Use data to drive measurable improvements in clinical operations (e.g., optimizing site selection, accelerating patient recruitment, and reducing trial timelines) • Move beyond traditional dashboards to develop novel, predictive, and prescriptive analytics that uncover hidden patterns and inform strategic decisions. • Collaborate with stakeholders to identify high-impact use cases where data can solve real business problems. • Implement right-sized data governance frameworks that balance agility with regulatory compliance. • Define data stewardship roles, metadata management practices, and data quality standards. • Lead data audits and ensure readiness for regulatory inspections. • Build and scale business intelligence platforms that deliver actionable insights to clinical and corporate stakeholders. • Enable internal functions (i.e., Clinical Data Sciences) by providing the data architecture, infrastructure, and tooling necessary to deliver study-level reporting and analytics to clients. • Partner with data scientists to deploy AI/ML models that improve forecasting, risk detection, and operational efficiency. • Champion the use of predictive analytics and automation to enhance trial execution and enterprise decision-making. • Build and mentor a high-performing data and BI team, including data engineers, analysts, and architects. • Foster a culture of data-driven decision-making and continuous improvement. • Communicate technical concepts and insights effectively to executive leadership and cross-functional teams.