ResponsibilitiesDefine, maintain, and evolve the Enterprise Data Architecture blueprint, including core enterprise data domains (Customer, Product/Material, Vendor, Pricing, Finance, Trade Compliance)Conceptual and logical enterprise data modelsCanonical data definitions and semanticsAct as Design Authority for all data‐related initiatives, ensuring alignment with enterprise architecture principlesDefine and enforce enterprise data standards (modeling, naming, semantics, integration)Collaborate closely with Enterprise, Solution, and Integration ArchitectsOwn the enterprise Master Data Management (MDM) strategy and execution roadmapDefine domain prioritization (e.G. Customer, Product/Material) and rollout phasesEstablish golden record, survivorship, hierarchy, and relationship‐management rulesLead the design and implementation governance of the selected MDM platformOversee data migration, cleansing, and harmonization activities linked to MDM adoptionEstablish and run the Enterprise Data Governance operating model, including data ownership and stewardship frameworkGovernance forums, decision bodies, and escalation mechanismsDefine and monitor enterprise data quality rules and KPIs (completeness, accuracy, uniqueness, timeliness)Implement structured data issue management and remediation processesEnsure data lineage, traceability, and auditability for critical business and regulatory dataDefine and maintain System‐of‐Record (SoR) / System‐of‐Engagement (SoE) principles across SAP (ERP, BW, GTS, Concur), Salesforce CRM, MES systems (e.G. Promis, Critical Manufacturing), Quoting and pricing platforms,



Finance, Treasury, AP automation, and EDI solutionsResolve data ownership conflicts and duplication at enterprise levelEnsure consistent and governed data synchronization patterns across systemsDefine enterprise canonical data models and data contracts for cross‐system integrationsGovern data flows implemented via SAP BTP, MuleSoft, and EDI platformsDefine integration patterns (API, event‐driven, batch, EDI) from a data semantics, integrity, and lifecycle standpointEnsure interface versioning discipline and backward compatibilityEnsure conformed dimensions and consistent master data usage across analytics and planning platforms (e.G. SAP BW)Align enterprise data definitions with KPIs, reporting, and planning use casesPrevent multiple and conflicting versions of enterprise truthTranslate architectural and governance decisions into executable implementation backlogsReview technical designs and ensure adherence to enterprise standardsCoordinate delivery with internal teams and external partnersRequirementsBachelor's or Master's degree in Computer Science, Information Systems, Engineering, or a related field10+ years of experience in Enterprise Data Architecture, Data Governance,



or related rolesDemonstrated experience in SAP‐centric enterprise landscapes integrated with multiple non‐SAP platformsProven experience designing and governing Master Data Management solutionsStrong background in enterprise integration concepts and data exchange patternsExperience operating in complex, global, and regulated environmentsEnterprise data modeling (conceptual, logical, canonical)Data governance frameworks and stewardship modelsMaster data and reference data managementData quality frameworks, metrics, and lifecycle managementIntegration data semantics (API‐led, event‐driven, batch, EDI)Solid understanding of SAP data concepts (Business Partner, Material, Finance, Pricing, BOMs, Routings)Strong stakeholder management, facilitation, and decision‐making skillsClear and structured documentation and communicationManufacturing and MES data architectureQuote‐to‐Cash and pricing data domainsTrade compliance and regulatory master data (e.G. export control, classification)Analytics and planning data architectureExperience leading small technical or architecture teamsDelivery focused with previous experience on at least one major data lake transitionEnterprise data ownership and governance model formally established and adoptedMeasurable improvement in master data quality and reduction in duplicatesSuccessful MDM/MDG rollout for prioritized domainsStable, reusable, and well‐governed data integration patternsImproved auditability, compliance, and reporting consistency #J-18808-Ljbffr

📌 Head Of Data Engineering & Analytics (Volpiano)
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📍 Volpiano