Principal Product Manager, Data Governance & Automation

The Position

Why Genentech: We’re passionate about delivering on Our Promise to improve the lives of patients and create healthier communities for all. We foster a culture of inclusivity, integrity and creativity while boldly pursuing answers to the world’s most complex health challenges and transforming society.

Who We Are: Our Data, Analytics, and AI team is dedicated to solving complex healthcare challenges and improving patient outcomes. Data, Analytics, and AI empowers business partners across Commercial, Medical, and Government Affairs (CMG) to make impactful decisions by leveraging data, analytics, business products, and AI/ML to enable fast, targeted actions in rapidly evolving business contexts.

Data, Analytics, and AI fosters a unified understanding of customers, actions, and outcomes by integrating analytics and insights seamlessly into CMG’s evolving digital, data, and automation platforms, creating scalable solutions and eliminating silos.

In Data, Analytics, and AI, you will work as a trusted, objective advisor and expert, recommending critical decisions and actions to be taken with credibility and a focus on driving measurable impact. You will be part of a thriving culture built on collaboration and innovation.

The Principal Product Manager, Data Governance & Automation in Data, Analytics, and AI is responsible for driving the development and implementation of data standards and governance frameworks that ensure the integrity, quality, effectiveness, compliance, and responsible use of data across the organization. In partnership with cross-functional stakeholders, this role leads the establishment, execution, and continuous improvement of data governance policies and procedures, and the vision and product roadmap of scalable technical solutions for data governance.

• Framework Implementation:
  Execute and refine data governance frameworks that support scalable data platforms, AI/ML initiatives, and self-service analytics across the business.
• Automated Quality Controls:
  Define rigorous data quality standards and design automated monitoring systems to ensure data accuracy, consistency, and validity across all assets.
• Technical Roadmap Execution:
  Lead the development of technical solutions for automated governance, including lineage validation, schema management, and "policy-as-code" enforcement.
• Regulatory Compliance:
  Manage ongoing compliance with HIPAA, GDPR, and CCPA through proactive risk mitigation, data masking, and regular audit programs.
• Access & Ethical Oversight:
  Establish and enforce data access practices, including Role-Based Access Controls (RBAC) and guidelines for ethical data usage.
• Metadata & Discoverability:
  Design scalable metadata and data lineage structures to improve data discoverability, ensuring assets are easily found and responsibly reused.
• Cross-Functional Integration:
  Partner with Engineering and Product teams to embed governance into the development lifecycle while driving company-wide data literacy and best practices.

• You have a Bachelor’s degree in a related field and 10+ years of experience in data governance, data management, automation engineering or related roles.
• You have deep knowledge of data quality frameworks and lifecycle management, with hands-on experience designing and building automated solutions for governance and quality assurance.
• You have proven ability to implement data governance policies and practices using Agile methodologies, successfully balancing business speed with regulatory compliance.
• You have demonstrated success leading cross-functional teams and influencing senior stakeholders to align technical governance goals with broader business objectives.
• You have strong problem-solving and communication skills with a track record of driving organizational adoption and leading teams through ambiguity in fast-paced environments.

Preferred:

• Advanced degree or equivalent experience (e.g., MBA or related graduate-level qualification).
• Experience with GxP and quality management systems in software development.
• Strong knowledge of big data or database technologies, relational and non-relational databases, SQL, and cloud-based…