Head of Data Engineering

We are seeking great talent to help us build The DNA of tech.® Vishay manufactures one of the world's largest portfolios of discrete semiconductors and passive electronic components that are essential to innovative designs in the automotive, industrial, computing, consumer, telecommunications, military, aerospace, and medical markets. We help the world's most in-demand technologies come to life. Every day our products touch your life and the lives of people across the world, though you likely do not know it. Come join us and help us build The DNA of tech.™

Vishay Intertechnology, Inc. is a Fortune 1,000 Company listed on the NYSE (VSH). Learn more at www.Vishay.com. Vishay Italy is currently seeking applicants for Head of Data Engineering & Analytics. In this position, you will be accountable for defining, governing, and evolving the enterprise‑wide data architecture across a complex, SAP‑centric application landscape. The role ensures that master, transactional, and analytical data are consistently defined, governed, integrated, and consumed across core platforms including SAP (ERP, BW, GTS, Concur), Salesforce CRM, MES systems, Quoting and Pricing platforms, Finance, Treasury, Trade Compliance, and Analytics. The role operates as the enterprise design authority for data, leads the data governance and MDM operating model, and manages a small team of data engineers to translate architectural decisions into sustainable execution.

Job Location: Vishay Semiconductor Italiana spa is site focused on the design, development and production of power diodes and power modules. There are around 300 employees currently work in Borgaro Torinese Italy. This number is constantly growing due to our expansion plans.

What You Will Be Doing

Define, 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 models
• Canonical data definitions and semantics
• Act as Design Authority for all data‑related initiatives, ensuring alignment with enterprise architecture principles.
• Define and enforce enterprise data standards (modeling, naming, semantics, integration).
• Collaborate closely with Enterprise, Solution, and Integration Architects.

Master Data & MDM Strategy Ownership

• Own the enterprise Master Data Management (MDM) strategy and execution roadmap.
• Define domain prioritization (e.g. Customer, Product/Material) and rollout phases.
• Establish golden record, survivorship, hierarchy, and relationship‑management rules.
• Lead the design and implementation governance of the selected MDM platform.
• Oversee data migration, cleansing, and harmonization activities linked to MDM adoption.

Data Governance & Data Quality

• Establish and run the Enterprise Data Governance operating model, including data ownership and stewardship framework.
• Governance forums, decision bodies, and escalation mechanisms.
• Define and monitor enterprise data quality rules and KPIs (completeness, accuracy, uniqueness, timeliness).
• Implement structured data issue management and remediation processes.
• Ensure data lineage, traceability, and auditability for critical business and regulatory data.

Cross‑Platform Data Consistency & System‑of‑Record Definition

Define 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 solutions

Resolve data ownership conflicts and duplication at enterprise level. Ensure consistent and governed data synchronization patterns across systems.

Integration & Data Semantics Governance

• Define enterprise canonical data models and data contracts for cross‑system integrations.
• Govern data flows implemented via SAP BTP, MuleSoft, and EDI platforms.
• Define integration patterns (API, event‑driven, batch, EDI) from a data semantics, integrity, and lifecycle standpoint.
• Ensure interface versioning discipline and backward compatibility.

Analytics & Reporting Alignment

• Ensure 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 cases.
• Prevent multiple and conflicting versions of enterprise truth.

Execution Oversight

• Translate architectural and governance decisions into executable implementation backlogs.
• Review technical designs and ensure adherence to enterprise standards.
• Coordinate del