Senior Director, Data, Cloud

Inventiva is a clinical-stage biopharmaceutical company headquartered in France, focused on the development of lanifibranor in a Phase 3 trial, NATiV3, in MASH. To learn more, please visit: https://inventivapharma.com/

The Opportunity

The company is seeking a hands-on technology leader to architect, build, and operate the data, cloud, and AI platform backbone that supports the Company’s clinical development, scientific research, medical, commercial, and corporate functions.The role participates in the IT leadership team and is accountable for its platform roadmap, budget, technical standards, and delivery outcomes.

Reporting to the CIO, the Senior Director owns the architecture, engineering, delivery, and technical operation of Inventiva’s data and AI platforms. This includes the underlying cloud environment, data integration and engineering capabilities, data warehouses, shared data services, AI platform infrastructure, and associated technical governance.

The role provides a secure, scalable, reliable, and cost-effective technology foundation that enables business and scientific teams to access trusted data and develop their own analytics, insights, and applications. This includes supporting clinical, medical, drug safety, biostatistics, and commercial data warehousing, while partnering closely with the respective functional teams on requirements, architecture, integration, and delivery priorities.

Key Responsibilities

• Lead enterprise data architecture and engineering supporting clinical, safety, medical, commercial, finance, and corporate functions.
• Design, build, and maintain scalable data warehouses, integration platforms, and shared data services.
• Establish standards for data ingestion, transformation, storage, governance, quality, lineage, and secure access.
• Enable integration and governed data exchange across internal systems, CROs, vendors, and external partners, ensuring compliance with contractual and regulatory requirements.
• Define common data models, interoperability standards, and centralized or federated architectures, applying FAIR principles where appropriate.
• Partner with functional data owners to establish priorities, accountability, and delivery milestones.
• Develop and maintain data platforms supporting Clinical Operations, Drug Safety, Pharmacovigilance, Medical Affairs, and Biostatistics.
• Integrate clinical and scientific data across EDC, CTMS, eTMF, safety databases, CRO platforms, and other relevant systems.
• Enable secure, governed access to trusted data for authorized reporting, analytics, and scientific applications.
• Establish technical controls for data quality, traceability, lineage, privacy, and regulatory compliance.
• Partner with functional stakeholders to translate business requirements into scalable platform solutions while maintaining functional ownership of reporting and analytical outputs.
• Support secure data exchange with CROs, research collaborators, and external partners.
• Lead the architecture, development, and maintenance of the commercial data warehouse and supporting infrastructure.
• Partner with Commercial Analytics to deliver scalable data capabilities supporting launch readiness and ongoing operations.
• Integrate commercial data sources, including CRM, claims, market data, patient services, and distribution systems.
• Establish data engineering standards, shared models, security, quality controls, and governed access.
• Maintain clear accountability between platform engineering and Commercial Analytics, which owns business insights, dashboards, reporting, and analytical products.
• Align platform development and delivery with commercial priorities and launch milestones.
• Lead architecture and technical operations of AWS environments supporting data, analytics, AI, and scientific workloads.
• Design secure, scalable, resilient, and cost-effective cloud infrastructure, including automation, identity integration, monitoring, and disaster recovery.
• Establish cloud cost management, performance optimization, and FinOps practices.
• Develop and maintain compute, data processing, and model-serving environments.
• Evaluate technology solutions, manage platform vendors, and oversee build-versus-buy decisions.
• Partner with IT & Operations to ensure alignment with enterprise infrastructure, security, and operational standards.
• Develop and execute the AI platform roadmap aligned with enterprise strategy and business priorities.
• Build and maintain secure, governed AI and machine-learning infrastructure, including model access, deployment, integration, and monitoring.
• Enable functional teams to develop and deploy approved AI applications through reusable platform capabilities.
• Establish