Global Data Product Lead - Supply Chain

At Sika, we are strengthening our global data capabilities across Supply Chain and Procurement. We are looking for an experienced Global Data Product Lead who combines strong end-to-end Supply Chain expertise with hands-on data engineering capabilities. 

This is a senior individual-contributor role with significant technical ownership and global exposure. You will lead through expertise while remaining hands-on, working closely with Procurement and Supply Chain stakeholders, Global Process Owners, IT, data teams, platform specialists and external engineering partners. You will design solutions, build critical components, guide external engineers and take ownership of maintaining the resulting data products beyond their initial delivery.

• Translate Procurement and Supply Chain requirements into clear, buildable data-product designs, working with business owners and Global Process Owners to clarify KPI definitions, calculation logic, source data, dimensions, and acceptance criteria.
• Design, develop, test, and maintain data pipelines, analytical data models, semantic models, dashboards, and data-quality controls that build reliable data foundations for global Procurement and Supply Chain key performance indicators.
• Assess source-system data and identify quality, availability, lineage, and integration issues; develop practical analytical and data-science solutions where they create clear business value.
• Build prototypes and critical solution components directly, and maintain and enhance productive data solutions as business requirements and source systems change.
• Define engineering standards, testing requirements, documentation, and technical acceptance criteria; ensure that solutions follow applicable architecture, security, access, deployment, and data-governance standards.
• Lead external data engineers when additional capacity or specialist expertise is required, including technical assessment, design review, code review, and knowledge transfer.
• Coordinate technical decisions with Mercury, IT, Data & Analytics, Enterprise Architecture, security, and relevant platform owners; challenge requirements and proposed solutions that create unnecessary complexity or cannot be maintained sustainably.
• Support portfolio prioritization based on business value, data readiness, technical dependencies, and available capacity, whilst contributing to a reusable data-product architecture.
• Monitor productive data products, investigate issues, implement corrective actions, and maintain documentation covering data models, lineage, business rules, quality controls, ownership, and support arrangements.