Genentech is seeking a Senior Manager, Facilities Data & Analytics to build and lead the data foundation for their Facilities & Engineering (F&E) organization. The goal is to transform how data is leveraged to enhance infrastructure reliability, optimize capital planning, and drive operational excellence across building and lab equipment assets, ultimately shaping and executing the long-term digital transformation of the F&E organization.
Requirements
- Familiarity with SAP CMMS (S4 Hana) required.
- Familiarity with ASPIRE SAP Finance System (S4 Hana) desired.
- Experience in dashboarding and analytics/dashboarding platforms (Tableau, SAC, etc.) required.
- Programming experience (Python, etc.) desired.
- Formal training in some level of statistics and/or statistical process control required.
- Experience with statistics modeling software such as JMP desired.
- Familiarity or working knowledge of reliability metrics (Mean Time Between Failure, Mean Time to Repair, etc) desired.
Responsibilities
- Oversee and manage a robust data governance framework for ~30,000+ assets, ensuring data quality, consistency, and accessibility across our asset management platform.
- Develop and scale a sophisticated analytics ecosystem, creating standardized reports, dashboards and predictive models that translate complex data into actionable insights for operational teams and strategic recommendations around capital investment, resource allocation and maintenance optimization for leadership.
- Act as a thought leader, identifying and championing the use of emerging technologies like AI and IoT to drive initiatives in predictive maintenance, resource optimization, and data-driven capital investment.
- Establish and enforce a consistent data governance process and master data standards across ~30,000+ assets for SSF and Dixon sites aligned with Quality and Global standards.
- Serve as a data specialist for our SAP CMMS/CCMS, overseeing data integrity and ensuring systems are continually inspection-ready and compliant with cGMP standards.
- Direct the development of a robust analytics toolkit, including standard reporting and advanced dashboards (Tableau, SAC, SEEQ, PiVision, etc), to support operational decision-making.
- Guide the application of AI across all phases of asset management—from initial generation of asset data through maintenance and reliability analysis to inform capital replacement.
Other
- Lead, coach, motivate and develop a high-performing team of ~4 employees including data specialists and reliability analytics experts.
- Given the highly regulated environment, ensure services comply with OSHA, cGMP, environmental, and other regulations.
- Collaborate across global teams to support the development of shared tools and processes across the network.
- Bachelor’s degree in engineering, data science, or a related field required.
- Demonstrated experience in leading teams of technical experts or data specialists is required.
