Product Owner

About the role

What you'll bring

• You have 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.
• You have ability to demonstrate a mix of technical skills and business processes knowledge and proven experience in rolling out a data product in multiple markets. Essential to have experience in data catalogue documentation and manage the product use throughout all the stages of the product lifecycle.
• You have strong experience working with Data Architects, Ingestion, Data scientists and visualization teams in an agile framework. Expert knowledge and demonstrated abilities to lead squads and tribes with ability to define user stories and prioritizing backlog in accordance with the Senior Product Owner’s vision of the product.
• You have strong ability to connect and federate distinct stakeholders in a complex organization, managing stakeholders from Global, Local, Business and IT colleagues.
• You are experienced implementing modern data strategies and solutions using cloud technologies (Azure, AWS, Google), Informatica Cloud, Databricks, Power BI or similar tools.
• You have capability to express complex data concepts into lay language for stakeholder management
• CYBELE Deployment
• Own the successful deployment of CYBELE PLM across regions, categories, and manufacturing sites, ensuring alignment with the global process m[KS2.1][SK2.2]odel and business objectives.
• Act as the primary IT representative for data deployment activities, driving scope decisions, deployment readiness, risk management, and stakeholder alignment throughout the programme lifecycle. Data Factory Management
• Lead Data Factory activities covering data scoping, profiling, cleansing, enrichment, validation, and migration readiness to support successful CYBELE deployments.
• Govern delivery priorities, resource allocation, execution plans, and performance metrics across Data Factory teams, deployment waves, and external partners.
• Drive continuous improvement of data quality, automation, and migration methodologies, leveraging lessons learned to scale delivery across future deployment waves. Support & Hypercare