About the Role:

As D&A Product Owner PLM, you will play a key role in delivering both the IT & Data mission and ambition by enabling business growth through technology and data.

The role begins with leading data delivery and deployment readiness for Cybele/PLM implementations and progressively transitions into full Data Product Ownership for the PLM ecosystem, ensuring trusted, governed, and business-value-driven data assets across R&I.

Technical Skills:

- Master's in CS / Engineering / Statistics / IT / Information Systems.

- 10+ years of total experience; 5-7 years in Data Product Management, agile, full product lifecycles (discovery delivery).

- Strong experience in the FMCG/Retail Data & Analytics Domain.

- Proven track record of implementing Data products related to Product Lifecycle Management (Ingredients, Semi Finished Goods, BOM, Packaging Items) and experience in integrating sources with standard MDM principles.

- Ability to demonstrate a mix of technical skills and business processes knowledge and proven experience in rolling out a data product in multiple markets.

- Experience in data catalogue documentation and managing product use throughout all stages of the product lifecycle.

- Strong experience working with Data Architects, Ingestion, Data scientists and visualization teams in an agile framework.

- Expert knowledge to lead squads and tribes with ability to define user stories and prioritize backlog.

- Strong ability to connect and federate distinct stakeholders in a complex organization.

- Experienced implementing modern data strategies and solutions using cloud technologies (Azure, AWS, Google), Informatica Cloud, Databricks, Power BI or similar tools.

Key Responsibilities:

1. CYBELE Deployment:

- Own the successful deployment of CYBELE PLM across regions, categories, and manufacturing sites.

- Act as the primary IT representative for data deployment activities, driving scope decisions, risk management, and stakeholder alignment.

- Ensure adoption of standardized PLM processes and data governance principles.

2. Data Factory Management:

- Lead Data Factory activities covering data scoping, profiling, cleansing, enrichment, validation, and migration readiness.

- Govern delivery priorities, resource allocation, execution plans, and performance metrics.

3. Support & Hypercare:

- Own post go-live support and hypercare activities, ensuring rapid issue resolution and business continuity.

- Coordinate cross-functional support teams to manage defects and prioritize remediation.

4. Data Migration:

- Define and oversee end-to-end data migration strategy, ensuring accurate, complete, and compliant transfer of product and master data.

- Drive data mapping, cleansing, digitization, and validation activities.

5. PLM Data Product Ownership:

- Own the vision, strategy, and roadmap for PLM data products and associated data assets.

- Partner with R&I business stakeholders to translate business needs into prioritized data capabilities.

- Define and manage data product backlogs, requirements, and value delivery metrics.

- Ensure data quality, governance, and metadata are embedded across the PLM landscape.

- Drive harmonization and standardization of PLM data across regions and functions.

- Oversee the lifecycle of PLM data assets, including enhancements, support, and continuous improvement.

- Monitor adoption, usage, and business value realization.

- Act as the primary steward and advocate for PLM data, driving data-driven decision making.