R&D Senior Product Owner Data Governance and Semantics

Job Context

As part of Chiesi’s global R&D transformation, we are building a unified R&D Data Ecosystem anchored by the creation of a next-generation central repository, data governance, and semantic platforms. This strategic initiative aims to bring together people, platforms, and processes to establish a trusted, connected, and intelligent data foundation for entire R&D.
By harmonizing data products enablement, governance, and semantics, we will enable consistent understanding and interoperability of scientific and operational data across domains, empowering insights, and cross-functional collaboration—turning fragmented information into a strategic asset.
The R&D Data Strategy, Enablement & Governance will oversee the management and governance of Chiesi's R&D data ecosystem and facilitate the entire cultural shift within R&D.

Purpose

The R&D senior product owner Data governance and semantics will lead data knowledge management strategy and execution for data governance and semantics to maximize the value of R&D Data. This role is both strategic and hands-on:  
you will define the semantic and quality aspect of the R&D Data Pipeline through metadata definitions, Data Catalogues creation, ontologies, knowledge graph and quality observability that make R&D data organized, discoverable and reliable. 
In collaboration with R&D functional SME and GICT, you establish and enforce governance processes, ensuring that R&D Data Pipeline is consuming high quality Data to drive new insights. Your influence will span scientific, and GICT teams as you champion a data-driven culture across R&D.

Main Responsibilities

1.    Semantic & Knowledge Strategy: 
- Lead the creation of semantic layer, data model, and ontologies that unify R&D data ecosystem with focus on clinical data domains. 
- Architect a knowledge graph that integrates heterogeneous R&D data.
- Ensure metadata and business glossaries are linked and machine-readable, enabling advanced data discovery and AI-driven insights.
2.    R&D Meta Data and Standardization: 
- Develop and implement a comprehensive R&D data governance framework. 
- Define policies, standards and best practices for data stewardship (roles, ownership, quality rules). 
- Work closely with functional SME (e.g. clinical, safety, CMC) to ensure data is defined, documented and maintained according to governance policies aligned with Chiesi Global guideline.
- Promote adoption of ALCOA+/FAIR principles.
3.   Data Product Ownership: 
- Define product requirements, prioritize features, and manage the backlog for data sets delivered by the engineering team. 
- Collaborate with engineers to oversee pipeline and schema changes so that outputs meet the needs of end users.
- Monitor product KPIs (data quality scores, usage metrics) and iterate on enhancements.
4.   Data Quality Management: 
- Establish R&D data quality frameworks: set validation rules, quality metrics and automated monitoring to ensure integrity of critical data.
- Integrate data quality checks (profiling, anomaly detection) into pipelines and alert stewards on exceptions.
5.   Stakeholder Engagement & Leadership: 
- Communicate the value of data governance and semantic initiatives at all levels. 
- Influence leaders by demonstrating how structured data and knowledge graphs improve research productivity and compliance.
- Act as a mentor and ambassador, resolving conflicts and balancing technical and business priorities.
6.   Continuous Improvement: 
- Establish metrics to track governance effectiveness (e.g. percentage of approved metadata, data quality improvements). 
- Review and refine governance policies over time. 
- Stay current on industry trends and recommend enhancements to processes and tools for continuous digital transformation of R&D.

Experience Required

o    Minimum of 5 years of experience in R&D clinical domain
o    Proven hands-on experience designing and implementing solutions in complex R&D environment.
o    Minimum of 3 years of experience in a Product Owner or similar strategic role, managing a product backlog and roadmap.
o    Strong background in data modeling techniques.
o    Experience working in the Pharmaceutical R&D or Life Sciences domain is highly preferred, with an understanding of R&D data flows and regulatory requirements.

Education

Advanced degree (Master’s/PhD) in Life Sciences, Data Science, or a related field. 

Languages

Fluent in English

Technical Skills

Technical Skills: Strong expertise in graph databases, semantic, and ontology platforms (e.g. neo4j, snowflake). Experience with data governance and metadata tools (e.g. Informatica),
Data Quality Management and data transformation (design and implementation of quality rules)
Product Management Skills: Proven product owner mindset with experience in agile environments. Able to write product requirements, define roadmaps, and deliver data solutions iteratively. Strong analytical skills to translate complex research needs into governable data products
Leadership & Communication: Excellent interpersonal skills with a track record of influencing without authority. Able to engage cross-functional teams (scientists, GICT,) and drive consensus. Strategic thinker with strong business acumen and the ability to articulate vision to executives and practitioners alike.

Soft Skills