Head of Data Engineering & Analytics

Vishay Intertechnology, Inc.

Head of Data Engineering & Analytics responsible for defining data architecture at Vishay. Governing MDM strategy and ensuring data quality across SAP and non-SAP platforms.

Posted 7/9/2026full-timeTorino • 🇮🇹 ItalyLeadWebsite

Tech Stack

Tools & technologies

ERP

About the role

Key responsibilities & impact

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 semantic
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.
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.
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.
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.
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.
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.
Translate architectural and governance decisions into executable implementation backlogs.
Review technical designs and ensure adherence to enterprise standards.
Coordinate delivery with internal teams and external partners.

Requirements

What you’ll need

Bachelor’s or Master’s degree in Computer Science, Information Systems, Engineering, or a related field.
10+ years of experience in Enterprise Data Architecture, Data Governance, or related roles.
Demonstrated experience in SAP‑centric enterprise landscapes integrated with multiple non‑SAP platforms.
Proven experience designing and governing Master Data Management solutions
Strong background in enterprise integration concepts and data exchange patterns.
Experience operating in complex, global, and regulated environments.
Enterprise data modeling (conceptual, logical, canonical)
Data governance frameworks and stewardship models
Master data and reference data management
Data quality frameworks, metrics, and lifecycle management
Integration 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 skills
Clear and structured documentation and communication
Manufacturing and MES data architecture
Quote‑to‑Cash and pricing data domains
Trade compliance and regulatory master data (e.g. export control, classification)
Analytics and planning data architecture
Experience leading small technical or architecture teams
Delivery focused with previous experience on at least one major data lake transition
Enterprise data ownership and governance model formally established and adopted
Measurable improvement in master data quality and reduction in duplicates
Successful MDM/MDG rollout for prioritized domains
Stable, reusable, and well‑governed data integration patterns
Improved auditability, compliance, and reporting consistency

Benefits

Comp & perks

health care coverage
financial support programs
other resources designed to help you achieve your personal and professional goals

ATS Keywords

✓ Tailor your resume

Applicant Tracking System Keywords

Tip: use these terms in your resume and cover letter to boost ATS matches.

Hard Skills & Tools

Enterprise Data ModelingData Integration PatternsData Quality FrameworksCanonical Data ModelsData MigrationData CleansingData LineageData Ownership ManagementData SemanticsData Issue Management

Soft Skills

Stakeholder ManagementFacilitation SkillsDecision-Making SkillsClear CommunicationStructured Documentation