Responsibilities
- Define and implement the data architecture vision for consumer and shopper data domains, enabling global standardization of models, workflows, and best practices across regions and product categories.
- Manage and mentor a worldwide team of data engineers, ensuring technical alignment, governance adherence, and a culture of collaboration and career development.
- Create, refine, and maintain data models for media and digital campaigns, eCommerce platforms, retail partners, and external data providers to support integrated and efficient data access.
- Convert business requirements into durable, scalable data architectures while anticipating potential data challenges and proposing forward-looking structural solutions.
- Supervise the development of data pipelines and exchange mechanisms using APIs, real-time feeds, and batch systems to ensure accurate, timely, and consistent data delivery.
- Champion compliance with master data management principles and advance data governance frameworks to produce reliable, consistent, and AI-ready data assets worldwide.
Responsibilities
- shaping and executing the data architecture strategy for the Consumer and Shopper domain, supporting global initiatives focused on standardizing data models, processes and practices across markets and categories.
- leading and developing a globally distributed team of Data Engineers, fostering technical consistency, governance compliance and a strong culture of engagement and professional growth.
- designing, evolving and documenting data models related to media and digital campaigns, eCommerce, retailers and third party data sources, enabling seamless data integration and efficient querying across consumer, customer and shopper data sets.
- translating business needs into scalable and robust data solutions, proactively identifying data related challenges and defining appropriate architectural responses.
- overseeing the design and implementation of data integration and exchange processes, leveraging APIs, data feeds and batch processing to guarantee reliable, timely and high quality data availability.
- playing a central role in ensuring adherence to master data principles and in continuously improving data governance standards, procedures and controls, with the objective of delivering globally consistent, trusted and AI ready data assets.
