Senior Product Manager – Manufacturing Technologies

The Senior Product Manager – Manufacturing Technologies is accountable for the value, adoption, reliability and lifecycle of the Factory Integration Layer (FIL) and related manufacturing and supply-chain integration capabilities.

In this role you will:

• Own the product vision, strategy, roadmap and lifecycle plan for FIL and related manufacturing and enterprise data integration capabilities.
• Lead your team in using approved AI tools to improve productivity and ways of working, role-modelling responsible use and follow GSK’s Responsible AI, privacy and security requirements.
• Partner with manufacturing sites, Business Process Owners, Quality, Engineering, Supply Chain, Digital and Data stakeholders to identify integration needs, process pain points, data dependencies and opportunities for standardization or reuse.
• Define outcomes and investment priorities for connectivity, orchestration, transformation, contextualization, event exchange, APIs and data delivery across shop-floor, site, edge, cloud and enterprise environments.
• Ensure FIL is positioned and managed as a scalable, reusable integration capability that supports priority manufacturing and CMC programs while avoiding unnecessary site-specific or program-specific customization.
• Develop outcome-based investment proposals covering value, scope, cost, benefits, risks, dependencies and success measures.
• Set prioritization guardrails for Product Owners and delivery teams and make roadmap trade-offs based on business value, compliance, operational continuity, reuse potential, urgency, capacity, technical dependencies and total cost of ownership.
• Coach Product Owners and peers, for example by reviewing their roadmaps and backlogs and sharing good practice, and drive high performance without formal authority.
• Partner with Enterprise, Solution, Data and Security Architects to define and govern reusable integration patterns, interface principles, canonical or semantic models, metadata expectations and architecture decision records.
• Promote consistent information models, data contracts, naming, lineage and contextualization practices, including alignment with enterprise ontology, knowledge-graph and unified namespace approaches where these support approved business outcomes.
• Establish measures for adoption, reuse, reliability, data quality, service performance, user experience and benefits realization.
• Embed observability, monitoring, support ownership, continuity, recovery and service-level expectations in the roadmap and definition of done.
• Ensure product initiatives satisfy applicable governance for cyber security, data protection, quality, validation, records management, change control, architecture, service readiness and operational resilience.
• Manage product risks, technical debt, obsolescence, duplicated interfaces and critical dependencies through appropriate governance.
• Lead capability-led technology and supplier evaluations and contribute to commercial decisions, statements of work and lifecycle planning without unnecessary vendor dependency.
• Drive adoption and operational readiness through onboarding, documentation, training, communications and support models.

Basic Qualifications:

• Bachelor's or Master's degree in Computer Science, Information Technology, Engineering, Data Science, Automation, Business, Life Sciences or a related discipline, or equivalent relevant experience.
• Significant experience in product management, digital manufacturing, integration platforms, data platforms, manufacturing technology, enterprise technology delivery, or a related discipline.
• Proven experience defining and managing product vision and roadmap for an integration platform, data capability, digital platform or comparable enterprise product.
• Experience translating manufacturing, business-process and user needs into product outcomes, reusable capabilities, investment proposals and prioritised roadmaps.
• Experience working across discovery, architecture, design, engineering, testing, validation, deployment, adoption, service transition and ongoing operation.
• Practical understanding of integration patterns such as APIs, events, messaging, orchestration, transformation, batch and streaming data movement, without dependence on a single vendor of technology.
• Experience with manufacturing and enterprise system landscapes and the challenges of connecting operational technology, site systems, enterprise applications and cloud or data environments.
• Experience applying data governance concepts including ownership, data contracts, metadata, lineage, quality, semantics and controlled access.
• Demonstrated ability to prioritise based on value, reuse, cost, risk, compliance, operational impact, capacity, and technical dependencies.
• Experience defining product and service measures and using adoption, reliability, data quality, support and user-experience insights to improve performance.
• Experience operating within governance requirements for architecture, cyber security, data protection, quality, validation, change control and service readiness.
• Experience influencing senior stakeholders and creating alignment across global functions, programmes and manufacturing sites.

Preferred Skills:

• Professional certifications in product management, agile delivery, enterprise architecture, integration, data management, cloud, service management, portfolio management or change leadership.
• Strong strategic product thinking with the ability to convert ambiguous business and integration challenges into clear product choices, roadmaps and decision guardrails.
• Strong communication, facilitation and influencing skills across manufacturing, business, architecture, data, engineering, quality and operational audiences.
• Ability to explain complex integration and data concepts in outcome-focused language for senior stakeholders.
• Commercial and financial acumen, including evaluation of cost, value, benefits, risk, licensing, supplier dependency and total cost of ownership.
• Ability to use evidence and product telemetry to challenge assumptions, prioritise investment and evaluate performance.
• Working knowledge of enterprise architecture, manufacturing systems, integration, data, cyber security, validation, service management and operational resilience.
• Commitment to technology-agnostic, capability-led evaluation and to simple, reusable, interoperable and supportable solutions.