Senior Knowledge Engineer

We are looking for an experienced Senior Product Owner – R&D Data Governance & Semantics to lead the strategy and implementation of data governance, semantic modelling and data quality capabilities across a complex Life Sciences R&D environment. This is a strategic and hands-on role, combining product ownership, data strategy and technical delivery. You will be responsible for establishing the frameworks, models and standards that make R&D data structured, discoverable, interoperable and trusted. Working closely with scientific, technical and business stakeholders, you will help shape how R&D data is defined, connected and governed, enabling more effective data use, advanced analytics and AI-driven applications. Key Responsibilities1. Data & Semantic StrategyDefine and implement a semantic strategy across the R&D data landscape.Develop data models, semantic layers, ontologies and controlled vocabularies to create consistency across complex data domains.Design and develop knowledge graph capabilities to connect disparate R&D datasets and improve data discoverability.Establish machine-readable metadata and business glossaries to support data discovery, analytics and AI applications.Translate complex scientific and business requirements into practical data and semantic solutions. 2. Data Governance & StandardisationDevelop and implement a comprehensive data governance framework across R&D.Define standards, policies and best practices covering data ownership, stewardship, metadata, definitions and quality.Work with subject matter experts across functions to ensure critical data is appropriately defined, documented and maintained.Establish clear ownership and accountability for R&D data assets.Promote recognised data management principles, including data integrity, traceability, accessibility and interoperability. 3. Data Product OwnershipOwn the strategy, roadmap and requirements for R&D data products and capabilities.Define product requirements, prioritise features and manage the product backlog.Partner with data engineers and technical teams to oversee development, pipeline changes and data model evolution.Ensure data products meet the requirements of scientific, business and technical users.Establish and monitor product KPIs, including data quality, adoption, usability and usage. 4. Data Quality & ObservabilityEstablish frameworks for measuring and improving the quality of critical R&D data.Define data quality rules, validation criteria and performance metrics.Embed automated data quality monitoring, profiling and anomaly detection into data pipelines.Identify data quality issues and work with data owners and technical teams to drive resolution.Continuously improve the reliability, consistency and usability of R&D data assets. 5. Stakeholder Management & LeadershipBuild strong relationships across scientific, technical and business functions.Communicate the value and business impact of effective data governance and semantic capabilities.Influence senior stakeholders and drive adoption of new data standards and ways of working.Translate complex technical concepts into clear business outcomes.Act as a subject matter expert and ambassador for effective R&D data management.Resolve competing priorities and build consensus across diverse stakeholder groups. 6. Continuous ImprovementEstablish metrics to measure the effectiveness and maturity of data governance and quality initiatives.Regularly review and improve governance frameworks, standards and processes.Monitor developments in data management, semantic technologies and AI.Identify opportunities to improve R&D data capabilities through new technologies, processes and operating models. Your BackgroundAdvanced degree (Master's or PhD) in Life Sciences, Data Science, Computer Science, Information Management or a related discipline.5+ years' experience working with data within an R&D or Life Sciences environment, ideally across complex scientific or clinical datasets.Proven hands-on experience designing and implementing data solutions within complex enterprise environments.3+ years' experience in Product Ownership, Data Product Management or a similar strategic role, including ownership of roadmaps, requirements and backlogs.Strong understanding of data modelling, metadata management and semantic technologies.Experience within Pharmaceutical, Biotechnology or broader Life Sciences R&D environments, with an understanding of complex data flows and regulated environments.Practical experience with knowledge graphs, graph databases, ontologies or semantic technologies.Experience with data governance, metadata management and data quality platforms.Strong understanding of data quality management, including the design and implementation of quality rules and monitoring frameworks.Experience working in Agile product environments, with the ability to translate complex requirements into practical, iterative data products.Strong analytical and problem-solving skills, with the ability to connect technical data challenges to scientific and business requirements.Excellent stakeholder management and communication skills, with the ability to influence without direct authority.Comfortable working across technical, scientific and business teams and engaging with stakeholders at both practitioner and senior leadership level.Strategic thinker with strong commercial and business awareness.Fluent English. What You'll BringYou will combine strong data expertise with genuine product ownership capability. The successful candidate will be comfortable moving between strategic discussions with senior stakeholders and hands-on conversations with engineers, data architects and scientific subject matter experts.Most importantly, you will be able to translate complex R&D requirements into structured, governed and usable data products that create tangible value for the wider organisation.