Job Purpose

As part of the Procurement Operations, Digitalization & Strategic Excellence team, the Procurement Data & Digital Excellence Specialist is responsible for building and maintaining the data foundations that enable modern, data-driven procurement operations.

The role ensures procurement data is accurate, reliable, governed, and accessible in real time to support operational excellence, advanced analytics, and AI-enabled capabilities. Working closely with procurement, IT, data engineering, and business stakeholders, the specialist will transform procurement data into a strategic asset that drives better decision-making and continuous improvement

Also, Bridgestone Europe is embedding AI across multiple ERP (mostly SAP - S/4HANA, BDC) landscapes and platforms. Within Procurement, this role delivers the data products that make those use cases possible: clearly defined, properly modelled, documented, and trusted.

Key Responsibilities

Data Governance & Stewardship

• Act as the Procurement Data Steward for master and transactional procurement data.
• Define, implement and continuously improve procurement data standards, governance and quality rules.
• Monitor data quality KPIs and drive corrective actions with business and IT teams.
• Ensure data consistency across SAP and connected procurement applications.

Data Foundation & Architecture

• Data Attribute Definition: Define and document data attributes, business rules, calculation logic, and field-level definitions for all procurement data products — spend, suppliers, contracts, and purchasing KPIs.
• Collaborate with IT and Data Platform teams to ensure procurement data is available, secure and scalable.
• Support the integration of SAP data with enterprise data platforms and analytical environments.
• Contribute to the evolution of procurement data architecture.
• Source-to-Target Validation: mappings from SAP S/4HANA and various data sources into SAP Business Data Cloud and Databricks, ensuring data flows correctly and completely.

Analytics & Business Intelligence

• Develop and maintain procurement dashboards, KPIs and self-service reporting solutions.
• Translate business requirements into actionable reporting and analytics.
• Support procurement category managers and leadership with insightful data analysis.
• Promote data-driven decision making throughout the procurement organization.

AI Enablement

• Ensure procurement data is AI-ready by improving its quality, structure and accessibility.
• Support the deployment of AI and Generative AI use cases within procurement.
• Partner with Digital and AI teams to identify opportunities for automation and predictive analytics.

Qualifications & Experience Required

Education, Master, other certification:

• Master’s degree in Data Science, Computer Science, Engineering, Information Systems, Statistics, or a related field.
• SAP certifications or proven experience in S/4HANA, BTP, Datasphere / Business Data Cloud, SAP Analytics Cloud, Databricks, or hyperscaler data platforms are a strong advantage.
• Training in data modelling, data governance, or AI and machine learning fundamentals is a plus.

Experience (years):

• 3-5 years in a data, analytics, procurement operations, or procurement technology role.
• SAP is essential: hands-on experience with S/4HANA procurement data structures, plus exposure to SAP Business Data Cloud, Datasphere, BTP, and SAP Business AI.
• Proven end-to-end delivery of data products, from definition to production, not one-off extracts.
• Hands-on experience with Databricks, Python, and SQL within a lakehouse or cloud data platform.
• Experience with integration and harmonisation of data across multiple or heterogeneous ERP systems.
• Experience preparing and governing data for AI, machine learning, or advanced analytics use cases.
• International, multi-country transformation programmes are a plus.

Technical Skills:

• SAP S/4HANA procurement data objects and master data: vendor, material, info records, source lists, contracts, purchase orders.
• SAP Business Data Cloud: data products, spaces, replication, consumption models; awareness of SAP Business AI, Joule, and AI Foundation on SAP BTP.
• Data modelling: relational and dimensional, semantic layers, canonical cross-system models, master data harmonisation.
• SQL and Python, including pandas and PySpark, for transformation, analysis, and automation.
• Databricks: notebooks, Delta Lake, workflows.
• Common data technologies beyond SAP: cloud data warehouses, ETL/ELT and orchestration, APIs, event-based integration.
• Architectural design at comprehension level: layering, lakehouse versus warehouse, batch versus real-time, and related trade-offs.
• Data governance: lineage, cataloguing, data contracts, and quality frameworks.
• SAP Analytics Cloud, Power BI, or Tableau; advanced Excel and PowerPoint.

Languages Skills:

• Fluent English, written and spoken.
• Additional European languages are a plus.

Soft/Behavioral Skills:

• Structured and precise, with rigour on definitions and documentation.
• Systems thinking: connects business process, data structure, and technology.
• Explains data and AI concepts clearly to non-technical stakeholders.
• Turns ambiguous business needs into scoped, deliverable data requirements.
• Curious about emerging data and AI technologies; comfortable with change and ambiguity.
• Strong ownership across multiple stakeholders and parallel deliverables.