Senior Data Product Manager

Genentech•South San Francisco, CA

8d•Hybrid

About The Position

The Senior Data Product Manager is responsible for the development, execution, and optimization of data products within the organization. This role focuses on translating business needs into data product requirements, managing the product lifecycle, and ensuring alignment with broader organizational goals. By collaborating with cross-functional teams, stakeholders, and business leaders, the Senior Data Product Manager drives data product enhancements and optimizes their impact across multiple use cases.

Requirements

Bachelor's degree in business, technology, operations, science, marketing, or a related field.
5 years of combined experience in product management, data management, AI, software development, or equivalent experience.
Demonstrated success managing product initiatives with a clear focus on driving tactical execution and operational improvements.
Proven ability to work effectively with cross‑functional teams to develop and execute product roadmaps, ensuring alignment on feature development and rollout.
Experience with sole ownership of tactics or product components, with the ability to articulate business problems, identify solutions, and drive execution from strategy through implementation.
Demonstrated ability to develop and execute product roadmaps, including feature planning, timelines, and dependencies.
Experience with User Acceptance Testing (UAT) and successfully rolling out new features across various user bases.
Strong analytical and problem-solving skills with experience in driving experimentation and optimization.
Proven success in aligning stakeholders and collaborating with cross‑functional teams to achieve seamless product integration.
Exceptional communication and presentation skills, with the ability to evangelize product vision and value across all levels of an organization.
Proven ability to adapt and navigate ambiguous or evolving environments.
Strong skills in budget management, resource allocation, and stakeholder alignment for cross-functional collaboration.
Analytical skills to interpret product usage data and system health metrics, driving actionable insights.
Strong knowledge of data quality frameworks, data governance principles, and data lifecycle management.
Knowledge of data governance frameworks and FAIR data principles.
Proficiency in data observability, data quality, data governance and data lineage tools (e.g., Informatica Data Quality, Collibra, MonteCarlo, etc.)
Strong knowledge of big data or database technologies, relational and non-relational databases, SQL, and cloud-based data platforms (e.g., AWS, GCP, Azure).

Nice To Haves

Advanced degree or equivalent experience (e.g., MBA or related graduate-level qualification).
Experience in digital product operations within mid‑to‑large enterprise environments.
A track record of effectively aligning and collaborating with stakeholders across multiple organizational levels.
Demonstrated ability to drive product innovation through structured experimentation and data‑driven decision‑making.
Experience in healthcare, pharmaceutical, or other highly regulated industries.
Ability to innovate and foster experimentation to improve product capabilities.
Certifications in data platforms or tools (e.g., AWS Certified Data Analytics, Tableau Desktop Specialist).
Experience with customer data strategy and an enterprise mindset in data management capabilities.
Experience in leading data or systems projects to drive design & establish best practices.
Advanced knowledge of workflow tools, automation systems, and compliance frameworks.
Strong problem-solving and adaptability to navigate ambiguous or evolving environments.

Responsibilities

Partner with the Principal Data Product Owner to support the creation of data product roadmaps, including features, timelines, and dependencies.
Develop and communicate a clear, value-driven product vision that aligns with broader organizational objectives and business needs.
Act as a point of contact for inquiries and demand requests related to our data products, effectively serving as the liaison between business stakeholders and the data product technology team.
Monitor and measure the performance of the data product in collaboration with IT partners, identifying opportunities for optimization and ensuring it consistently delivers value to stakeholders.
Collaborate with cross-functional teams and technology partners to identify and acquire data sources that meet business product requirements and strategic objectives, ensuring alignment with broader data enablement strategies.
Maintain and prioritize the data product backlog, ensuring it addresses the requirements of both single and multiple business use cases enabled by the product.
Collaborate with cross-functional teams to design, test, and release data product enhancements, ensuring data quality, usability, and seamless integration with business workflows.
Guide the cross-functional team in adhering to data mesh and data fabric principles, ensuring the product complies with established standards and supports scalability.
Engage with business leaders and end-users to advocate for the data product, fostering trust and collaboration.
Facilitate the adoption and integration of tools and platforms that support data exploration, analytics, and visualization, in collaboration with technical counterparts.
Establish and maintain a comprehensive data quality framework that aligns with Genentech's strategic objectives and regulatory requirements.
Collaborate with data governance teams to ensure proper stewardship and accountability for data assets.
Define key data quality metrics and partner with relevant teams to ensure visibility into data integrity and performance.
Identify, prioritize, and address data quality issues, driving root-cause analysis and remediation efforts.
Partner with data stewards, data engineers, and business units to understand data needs and challenges.
Act as a liaison between technical and non-technical teams to ensure alignment on data quality priorities.
Foster a culture of data excellence by providing training and education on data quality best practices.
Oversee compliance with data governance policies, ensuring adherence to regulatory standards such as HIPAA, GDPR, and other industry guidelines.
Comply with all laws, regulations and policies that govern the conduct of Genentech activities.