Director, Quality Data Governance & Technology

The Director Quality, Data Governance & Technology is a senior Quality leadership role accountable for enterprise-wide Quality oversight of Computer System Validation (CSV) activities across Bio Marin's IT systems and applications, and for owning and continuously improving the CSV program in collaboration with the DTA (Digital Technology and AI) team. This role is equally accountable for leading Bio Marin's Data Governance and Data Integrity program, driving the design, effectiveness, and continuous improvement of data governance measures, global compliance and process performance.

Cross-functional collaboration with partners and stakeholders across sites and functions is key to success in this role. This includes close partnership with data experts and stakeholders across engineering, computer system validation, manufacturing, data sciences, QC, QA, Compliance, and DTA. In collaboration with these SMEs and stakeholders, the Director ensures that all processes impacting computer software validation, data governance, and data integrity are compliant, agile, and support the evolving needs of the business.

This role is also a driving force behind Bio Marin's digital and AI advancement within Quality. The Director partners with DTA, Data Science, and business stakeholders to identify, evaluate, and scale emerging technologies, including AI, machine learning, automation, and advanced analytics, ensuring Bio Marin remains at the forefront of regulatory expectations while unlocking potential across the Quality organization. This is an exciting time to step into this role, as AI rapidly reshapes how Quality Processes can operate, the Director will have the opportunity to shape how Bio Marin harnesses these technologies responsibly, positioning the organization at the leading edge of this transformation.

This position requires in-depth knowledge and experience with computer system validation, data governance, and data integrity, along with a high-level understanding of other quality management system processes. The leader must possess strong leadership qualities, business acumen, and technical expertise in the areas of responsibility, together with a solid understanding of developments in data science and emerging technologies such as AI, machine learning, and cloud computing, to address complex challenges in a pharmaceutical environment.

• Provide leadership and direction to a team of Quality Engineers responsible for Quality oversight of computer software validation activities for enterprise-wide systems and applications. Ensure appropriate resource support to manage established portfolio of projects.
• Co-lead continuous improvement of the CSV program, standardizing methodologies, requirements, and lifecycle approach within a harmonized and simplified QMS environment.
• Evolve the CSV program's execution model to be ready for a future where AI plays an increasing role in system validation, reassessing methodologies, controls, and resourcing so the program can efficiently and compliantly validate AI-enabled systems and leverage AI-assisted validation tools as they mature.
• Ensure CSV/CSA activities are interconnected, aligned, and streamlined with policies and procedures established by DTA and CSV, applying a System Development Lifecycle approach commensurate with system complexity, risk, and intended use.
• Establish global KPIs and oversee trending of key performance metrics associated with the CSV program; support Quality Management Review activities; report and elevate compliance issues to management.
• Partner with Compliance on site and global Quality inspections, providing SME support related to CSV activities and related observation responses.

• Develop, own, and continuously improve a comprehensive and compliant Data Governance / Data Integrity program for Bio Marin, accountable for its design and overall effectiveness.
• Implement the data governance framework under a Data Governance Master Plan, in collaboration with cross-functional teams including IT, manufacturing, technical development, quality assurance, and R&D; align and gain sponsorship from leadership and stakeholders.
• Define deliverables for the implementation of enhanced data governance measures to enable data integrity assurance by-design, ensuring solutions are purposefully integrated into business processes to drive adoption.
• Optimize…