Principal Fellow, Data Engineering

• Define and execute enterprise-wide data platform strategy and architecture roadmap
• Modernize legacy systems to cloud-native, scalable solutions
• Design secure, high-performance data platforms compliant with HIPAA, GDPR, SOC2, and enterprise security standards
• Lead adoption of data Lakehouse architecture, unified data catalogs, SQL analytics, and AI/ML frameworks
• Establish data governance frameworks including data lineage, quality standards, and role-based access controls
• Lead implementation of generative AI, retrieval-augmented generation (RAG), and agentic AI solutions
• Design enterprise AI architecture leveraging large language models, vector databases, AI agents, and model governance
• Establish DataOps, DevOps, and MLOps frameworks, reusable architecture patterns, and CI/CD pipelines
• Partner with executive leadership on architecture roadmaps, business cases, and transformation strategies
• Mentor architects, engineering managers, and technical leads
• Build and grow a Center of Excellence for data, analytics, and AI technologies
• Lead strategic vendor partnerships and technology evaluations
• Drive strategic data platform modernization and AI innovation across clinical research operations and business intelligence

• Bachelor’s degree in computer science, Engineering, Data Science, or related field, or equivalent professional experience
• 12+ years of experience in enterprise data architecture, data engineering, cloud platform design, or related technical leadership roles
• Demonstrated expertise in designing and implementing data platforms, data warehouses, or data lakes at enterprise scale
• Strong knowledge of cloud platforms (AWS, Azure, or GCP) and modern data technologies
• Experience with governance frameworks, data quality standards, and regulatory compliance in healthcare or regulated industries
• Proven ability to lead cross-functional teams, influence organizational strategy, and drive technology adoption
• Excellent communication, strategic thinking, and problem-solving skills
• Experience working in healthcare, life sciences, regulated environments, or large-scale enterprise settings
• Comfort working with modern cloud platforms, distributed systems, and emerging AI/ML technologies
• Patient-focused mindset and commitment to using technology to advance clinical research and patient outcomes

• Flexibility and growth opportunities
• Continuous learning opportunities
• Opportunities to explore emerging technologies and expand expertise in AI and cloud platforms
• Opportunities to advance into strategic leadership roles
• Opportunity to shape the future of clinical research technology and influence organizational strategy