R&D Product Owner - Data, Analytics, Digital & AI Delivery (Pharma Industry)

With deep expertise in SAP S/4HANA and SAP ECC, ERP Logic supports businesses in transitioning to advanced ERP systems with a customer-centric approach and sustainable solutions.\n\nRole Description\nThe DADAI (Data, Analytics, Digital & AI Delivery) Domain Product Owner is accountable for translating approved product priorities into delivery-ready scope and for maximizing execution quality across products. The Product Owner owns the product backlog, clarifies requirements, defines acceptance criteria, and ensures delivery teams can execute with clear priorities, technical alignment, and quality standards.\nThe Product Owner acts as the primary delivery-facing interface between the domain Business Unit priorities (via the IT SHM / Product Manager) and the DADAI delivery factory / CoEs at the product level, ensuring continuous alignment between business intent, delivery execution, and backlog refinement.\n\nKey Responsibilities\nThe Product Owner contributes execution input required for delivery planning, including:\n· Translating approved business priorities into clear product scope, epics, features, and user stories.\n· Identifying execution implications and collaborating with CoEs, Architecture, Data, and delivery teams to refine delivery-ready scope\n· Assessing execution dependencies, technical constraints, regulatory considerations, and data readiness implications at product level\n· Defining clear feature scope, acceptance criteria, assumptions, and delivery readiness inputs for planning\n· Ensuring backlog items are complete, clear, and meet DADAI quality standards prior to PI / sprint planning and delivery execution\n· Acting as the primary delivery-facing product authority for feature scope, backlog priorities, and acceptance decisions for ARTs, PODs, and vendor teams\n· Supporting operational feedback loops by translating production learnings, defects, and enhancement requests into backlog refinement and prioritized delivery actions\n\nSuccess Measures:\nDelivery Readiness & Planning Quality\n· Percentage of features entering PI / sprint planning with clear scope, acceptance criteria, dependencies, and required architectural or data inputs identified.\n· Minimizing late discovery of dependencies, data readiness gaps, or scope ambiguity during planning and execution.\nExecution Quality\n· Plan adherence of sprint / PI predictability for committed feature delivery.\n· Percentage of accepted stories / features meeting definition of done without major rework.\n\nEducation and Skill-set Required\nData, Analytics, Digital, Automation or AI Products (5+ years)\n· Proven ability to understand existing systems and data landscapes, business processes, integrations, and translate business needs into scalable digital, data, and AI solutions.\n· Proven experience in business analysis and delivery for enterprise digital, data, analytics and AI solutions within complex, global organizations.\n· Strong understanding of end‑to‑end data and analytics lifecycles, including data ingestion, modeling, transformation, analytics consumption, and operationalization of insights.\n· Hands-on experience supporting the design, implementation, and adoption of business applications, and workflow‑based digital solutions across multiple business units.\n· Experience working with analytics, AI, and ML-enabled solutions, including requirements definition, use‑case shaping, model integration into business processes, and alignment with platform and data governance standards.\n· Solid knowledge of data concepts such as data modeling, data integration, data quality, and working with structured datasets to support reporting, advanced analytics, and AI use cases.\n· Strong understanding of relational databases and querying concepts (e.g., SQL or similar technologies), with the ability to collaborate effectively with data engineers and analytics teams.\n· Broad understanding of enterprise cloud ecosystems, including productivity platforms, data platforms, and cloud services supporting analytics and AI workloads.\nProduct Ownership in Enterprise IT (5+ years)\n· Enterprise IT roles combining business‑facing product ownership with delivery execution\n· Proven ability to operate within domain priorities while managing product‑level tradeoffs and dependencies\nBacklog Refinement & Delivery Readiness (5+ years)\n· Proven experience translating approved business priorities into epics, features, and user stories that are ready for delivery planning, including:\no Feature decomposition and backlog structuring\no Acceptance criteria definition and readiness for planning\no Dependency, technical constraint, and data readiness identification\no Preparation of delivery-ready inputs for PI / sprint planning\no Demonstrated ability to work in close partnership with a business‑facing leader (IT SHM / Product Manager) while owning backlog clarity, delivery readiness, and execution quality.\nTechnical Assessment & Data Quality (5+ years)\n· Capability to perform high‑level technical assessment of data, digital and AI solutions, including dependencies, constraints, and implementation implications.\n· Strong focus on data quality assurance, including alignment on data definitions, quality checks, and acceptance metrics across the data pipeline and analytical outputs.\n· Hands‑on experience driving product alignment with:\no Enterprise Architecture\no Security and privacy\no Data governance\n\nAdvantage - Domain Business Understanding (3+ years)\n· Hands‑on experience delivering, or product‑owning solutions in the pharma R&D business area.\n· Strong ability to translate business processes and pain points into epics, features, and measurable product outcomes.\n\nPreferred\nRegulated or High‑Compliance Environment (2+ years)\n· Experience delivering solutions in environments with:\no Validation requirements\no Audit readiness\no Controlled release and change management practices (e.g., GxP)\nFormal Certifications\n· SAFe POPM, SAFe Practitioner, or equivalent agile/product certification.\n· ITIL Foundation or equivalent service management exposure.\n\nKey Capabilities and Skills\n· Strong stakeholder management and communication skills\n· Ability to translate business problems into clear, delivery-ready requirements\n· Value-focused prioritization and decision-making\n· Structured, detail-oriented, and comfortable working with ambiguity\n· Collaborative mindset with delivery teams and business partners\n· Demonstrated proficiency in data analysis, digital technologies, and AI literacy\n· Understands enterprise platforms and constraints\n· Can assess technical impact of scope & priority decisions\n· Ensures quality and operability are built into the product\n· Effective collaboration with engineers, architects, and Scrum / ART roles to remove ambiguity and enable predictable delivery