Configurable Materials Master Data Domain Lead

We are looking for a Configurable Materials Master Data Domain Lead whose core craft is Variant Configuration. SAP VC, including characteristics, classes, configuration profiles, dependencies, constraints, and super-BoMs, is the structural spine of how we define, price, manufacture, and service our products worldwide. You will own the strategic data roadmap for this domain, serve as Business Owner for SAP MDG-M and the SAP Variant Configuration landscape (LO-VC / AVC), and orchestrate cross-functional initiatives that enable product innovation, operational excellence, analytics, and intelligent automation. This is a global role, reporting directly to the Global Head of Data Governance & MDM, with end-to-end accountability across R&D, Commercial, Procurement & Operations, and Finance, spanning Idea-to-Market (I2M), Market-to-Cash (M2C), Plan-to-Deliver (P2D), and Record-to-Report (R2R). If you have deep VC-modeling expertise and want to shape how a world-class industrial company builds its digital product thread, we want to hear from you.

• Own and evolve the SAP VC data model as the central spine of dormakaba's product definition: characteristics, characteristic values, classes, configuration profiles, object dependencies, constraints, and variant tables.
• Drive the strategic evolution from classic LO-VC toward Advanced Variant Configuration (AVC), defining the migration roadmap, capability gaps, and business-case priorities together with the Global Process Experts and Enterprise Architecture.
• Design and govern super-BoM and variant-BoM structures that translate configurable product definitions into executable manufacturing and procurement plans across global plants.
• Define and maintain the material classification, codification, and hierarchy frameworks that underpin VC model selection and variant determination at scale.
• Own the material-side BoM data strategy and mastership rules across the full digital thread: from engineering-BoM origins in PLM, through manufacturing-BoM refinement in ERP, to shop-floor execution in MES.
• Build long-term standards for BoM structure, revision control, change propagation, and deviation management, ensuring a single source of truth that evolves with our product portfolio.
• Architect integration patterns across the materials ecosystem (PLM Windchill, SAP MDG, S/4HANA, PIM/DAM, MES) with a focus on data consistency, real-time synchronization, and API-first connectivity.
• Ensure the VC model drives accurate, scalable variant pricing by linking configuration logic to pricing procedures, condition techniques, and commercial rules in S/4HANA.
• Support the integration of VC-based product models into CPQ platforms and digital sales channels, enabling self-service configuration with validated, real-time data.
• Extend the materials master-data domain toward serialized equipment, service BoMs, and spare-parts management.
• Define how VC-derived product structures translate into installed-base records and service-kit definitions, ensuring traceability from original configuration to aftermarket offerings.
• Embed material composition, weight, and substance data into the materials master record to support sustainability reporting and environmental compliance requirements.
• Ensure compliance-related data (REACH, RoHS, and future regulations) is structurally linked to the VC model and BoM, enabling automatic variant-level compliance determination.
• Drive the data standards that allow dormakaba to answer regulatory, customer, and investor questions about product composition and traceability.
• Own the strategic roadmap for Configurable Materials master data, aligning it with dormakaba's business, digitalization, and sustainability ambitions.
• Evolve the global materials governance framework, including data ownership, stewardship, policies, and standards.
• Champion data product thinking by treating master-data assets as products with defined consumers, SLAs, lineage, and lifecycle management.
• Apply modern data architecture principles to create a scalable and interoperable materials data ecosystem.
• Build and sustain an active external stakeholder network to benchmark practices and introduce emerging industry standards.
• Act as Business Owner for SAP MDG-M and the SAP Variant Configuration landscape (LO-VC / AVC), shaping their evolution to meet current and future business requirements.
• Lead the materials master-data workstream within RECITE, dormakaba's global S/4HANA transformation, driving template design, localization requirements, testing, and master-data harmonization.
• Serve as the direct data-domain counterpart to the onePLM program, ensuring PLM-to-ERP mapping, BoM synchronization, and digital-thread alignment.
• Apply AI and intelligent automation to improve profiling, stewardship, anomaly detection, and rule management within the materials domain.
• Lead the materials master-data community across dormakaba through structured communication, training, engagement, and change-management initiatives.
• Define and implement a fit-for-purpose operating model for the materials data domain, optimizing the interplay of onshore, near-shore, and offshore resources.
• Mentor and guide the materials data team, fostering accountability, continuous learning, and cross-functional collaboration.

• You are a deep craftsperson in Variant Configuration and materials master data who can navigate complex global matrix organizations, build consensus among senior stakeholders, and translate intricate VC and BoM concepts into business value.
• You challenge the status quo constructively and energize others to follow.
• AI is a powerful multiplier in your hands; the VC model and the material master are the core you will never delegate to a tool.
• 8–10 years of hands-on materials master-data and Variant Configuration leadership in multinational corporations, with a proven track record in configurable-products industries (industrial technology, engineered products, or similar).
• Deep expertise in SAP LO-VC and a clear point of view on the evolution path toward AVC, including the data-model, process, and governance implications.
• Demonstrable mastery of VC modeling objects: characteristics, classes, configuration profiles, object dependencies, constraints, variant tables, and their interplay in super-BoM and variant-BoM structures.
• University degree in Data Management, Information Technology, Supply Chain, Engineering, Finance, or a related discipline.
• Explicit experience owning BoM data strategy and mastership across PLM, ERP, and MES boundaries — engineering-BoM, manufacturing-BoM, and the change-propagation standards that keep them synchronized.
• Strong understanding of data modelling, data architecture, and integration patterns.
• Familiarity with modern data-management disciplines: data governance, data quality, data lineage, metadata management, data cataloguing, data observability, and data-mesh / data-fabric concepts.
• Proven track record of leading data-quality improvement programs at scale, including data cleansing, standardization, and harmonization in global environments.
• Experience working in or designing Shared Services and global delivery models.
• Demonstrated ability to engage external stakeholders — industry forums, standards organizations, peer networks, and strategic partners — to benchmark practices, introduce innovation, and elevate internal data-management standards.
• Comfortable applying AI/ML as an accelerator on top of deep domain expertise — e.g., intelligent profiling, automated rule generation, and agentic process automation — while maintaining ownership of the underlying VC and material-master logic.
• Excellent stakeholder-management, communication, and presentation skills; fluent in English (written and spoken).
• Pragmatic project-management skills with the ability to run multiple workstreams in parallel and deliver on time in ambitious transformation programs.
• Experience with PLM (Windchill or similar), PIM/DAM, and MES ecosystems is highly desirable.
• Knowledge of SAP Signavio and LeanIX is advantageous.
• Advanced qualifications (e.g., CDMP, DAMA-DMBOK, or SAP certifications) are a plus.
• German language skills.