Role Purpose The Data & Knowledge Steward will be responsible for defining, structuring, and maintaining the data "fuel" required for our app to operate effectively. This includes designing taxonomy, tagging, and metadata frameworks , ensuring data is accurate and usable, and anticipating future data requirements as the product evolves. This is not a traditional Product Owner or technical engineering role it is a data-centric, insight-enabled role focused on structuring information for AI-driven use cases . Key Responsibilities Data Definition & Structuring Define what data is required to support current and future app use cases Design and implement taxonomy, tagging, and metadata frameworks Structure food, ingredient, nutritional, and behavioural data for AI consumption Establish standards for data classification, organisation, and relationships Data Stewardship & Quality Act as the custodian of the apps data and knowledge model Ensure data is accurate, complete, consistent, and well-maintained Implement and uphold data quality and governance principles Identify and resolve gaps or inconsistencies in underlying datasets Data Sourcing & Curation Source and curate data from internal stakeholders (e.g. product, marketing, food teams) Integrate external data sources where relevant (e.g. suppliers, nutritional databases) Build relationships across the business to unlock and access relevant data Future-Focused Data Enablement Anticipate future product features and ensure the required data is available ahead of time Translate business scenarios into data requirements and structures Continuously evolve the data model to support new use cases and capabilities Collaboration Work closely with product, data science, and engineering teams Translate business needs into structured, usable data frameworks Support AI/ML teams by ensuring high-quality, well-structured input data Required Experience & Skills 5+ years experience in a data-focused role such as: Data Steward / Data Governance Metadata Management Information Architecture Knowledge Management Content / Taxonomy Design Strong understanding of: Taxonomy, tagging, and metadata frameworks Data classification and structuring principles Data quality and governance Experience working with structured and semi-structured data Ability to translate business needs into data requirements and models Strong stakeholder engagement and cross-functional collaboration skills Nice to Have Experience in retail, eCommerce, or customer-facing digital platforms Exposure to AI/ML or data-driven products Familiarity with: Master Data Management (MDM) Ontologies or knowledge graphs SQL or data querying What Good Looks Like Thinks in structures, categories, and relationships Naturally asks: "How should this data be organised so a system can use it?" Comfortable working with ambiguity and evolving requirements Strong curiosity around how data enables intelligent systems