Clinical Data Engineering Lead

Novartis Biomedical Research (NBR) is searching for a visionary Associate Director to lead Clinical Data Engineering within our Oncology Data Science (OncDS) team. In this pivotal role, you’ll be at the forefront of shaping early clinical development by building innovative biomarker data infrastructure, championing translational research, unlocking AI-powered discoveries, and raising the bar for operational excellence in biomarker data and multimodal analytics across Novartis’ oncology trials.

What You Will Do

Define and implement the clinical data engineering roadmap, integrate advanced tools and AI/ML-ready infrastructure, align clinical and pre-clinical data engineering initiatives with the broader oncology strategy, lead, manage, and develop a high-performing clinical data engineering team, drive strategic initiatives and partnerships across a matrixed organization, oversee data ingestion, transformation, and validation processes, collaborate with CROs and internal teams to optimize data flow, versioning, and retention policies, build and optimize data pipelines for both structured and unstructured clinical data.

Why It Might Be a Fit

This role requires a Master's degree in computer science, Bioinformatics, Data Engineering, Software Engineering or a closely related discipline, with a minimum 10 years of hands-on experience architecting and managing clinical data engineering, data management, and bioinformatics solutions in pharmaceutical or biotechnology industry, demonstrated expertise in designing, implementing, and scaling data infrastructure to support clinical development, including AI/ML-driven analytics and multimodal data integration, proven ability to define, document, and operationalize end-to-end assay data generation and processing pipelines, with a focus on automation, orchestration, and compliance, deep familiarity with FAIR data principles, data harmonization, and enterprise data governance frameworks, strong leadership in technical teams, with advanced communication and stakeholder management skills.

Requirements

• Master's degree in computer science, Bioinformatics, Data Engineering, Software Engineering or a closely related discipline
• Minimum 10 years of hands-on experience architecting and managing clinical data engineering, data management, and bioinformatics solutions in pharmaceutical or biotechnology industry
• Demonstrated expertise in designing, implementing, and scaling data infrastructure to support clinical development, including AI/ML-driven analytics and multimodal data integration
• Proven ability to define, document, and operationalize end-to-end assay data generation and processing pipelines, with a focus on automation, orchestration, and compliance
• Deep familiarity with FAIR data principles, data harmonization, and enterprise data governance frameworks
• Strong leadership in technical teams, with advanced communication and stakeholder management skills

Benefits

• Comprehensive benefits package
• 401(k) with company contribution and match
• Generous time off package including vacation, personal days, holidays and other leaves
• Performance-based cash incentive
• Annual equity awards