> Markdown version of [/jobs/ext/1270055-head-of-data-engineering-analytics](https://www.wearedevelopers.com/jobs/ext/1270055-head-of-data-engineering-analytics). Every page supports `.md` or `Accept: text/markdown`. Links point to the HTML versions so they work for humans too. Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # Head of Data Engineering & Analytics - **Company:** Vishay - **Location:** Malvern, PA, United States - **Experience:** Expert - **Contract:** Permanent contract - **Skills:** Application Programming Interfaces (APIs), Data Analysis, Audit Trail, Information Systems, Data Architecture, Data Governance, Data Migration, Data Synchronization, Electronic Data Interchange (EDI), Salesforce.Com, SAP (Applications), SAP NetWeaver Business Warehouse, SAP NetWeaver Data Management, Data Streaming, Systems Integration, Management of Software Versions, Enterprise Data Management, PROMIS, SAP Business Technology Platform, Data Lakes, Information Technology, Data Lineage, Data Analytics, Enterprise Integration, Data Management, Mulesoft - **Published:** July 15, 2026 - **Apply:** https://www.indeed.com/viewjob?jk=308efdd1c4009d5b ## About the Role 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 ## Description 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. 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 delivery with internal teams and external partners. ## Related Videos - [Empowering Retail Through Applied Machine Learning](https://www.wearedevelopers.com/videos/976-empowering-retail-through-applied-machine-learning) - [Why make use of an integration platform in today's software developments and infrastructure?](https://www.wearedevelopers.com/videos/758-why-make-use-of-an-integration-platform-in-today-s-software-developments-and-infrastructure) - [Blueprints for Success: Steering a Global Data & AI Architecture](https://www.wearedevelopers.com/videos/1577-blueprints-for-success-steering-a-global-data-ai-architecture) - [The Eventloop in JavaScript - How does it work?](https://www.wearedevelopers.com/videos/1211-the-eventloop-in-javascript-how-does-it-work) - [The Data Mesh as the end of the Datalake as we know it](https://www.wearedevelopers.com/videos/156-the-data-mesh-as-the-end-of-the-datalake-as-we-know-it) - [The Sustainability Race: AI's Promises, Pitfalls and Potential](https://www.wearedevelopers.com/videos/100155-the-sustainability-race-ai-s-promises-pitfalls-and-potential) ## Related Articles - [Top Big Data Technologies That You Need to Know](https://www.wearedevelopers.com/magazine/108-top-big-data-technologies-that-you-need-to-know) - [Making Data Warehouses Fast: A Developer’s Story](https://www.wearedevelopers.com/magazine/107-making-data-warehouses-fast-a-developer-s-story) - [Highest Paying Tech Companies for Developers](https://www.wearedevelopers.com/magazine/220-highest-paying-tech-companies-for-developers) - [The Most Popular IT Jobs on the Market](https://www.wearedevelopers.com/magazine/376-the-most-popular-it-jobs-on-the-market) - [Now is the time for industrialized software development](https://www.wearedevelopers.com/magazine/601-now-is-the-time-for-industrialized-software-development) - [Top-Paying Tech Jobs (with Salaries)](https://www.wearedevelopers.com/magazine/372-top-paying-tech-jobs-with-salaries)