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# Head of Data

- **Company:** SIEMENS ENERGY LIMITED
- **Location:** UK
- **Experience:** Expert
- **Contract:** Permanent contract
- **Skills:** Artificial Intelligence, Audit Trail, Data Infrastructure, Graph Database, DataOps, Data Classification, Data Layers, Information Technology, Data Management
- **Published:** October 30, 2026
- **Apply:** https://www.careerjet.co.uk/job/gb90ab4e8c3a08c41ba6cd574d16bac595/eaa

## About the Role

* A university degree in computer science, engineering, mathematics, business, or a related field
 * Extensive leadership experience across data platforms, data product ecosystems, governance, and enablement in complex enterprise environments
 * Deep expertise in data foundations for AI, including data products, DataOps, semantic/knowledge graph layers, access controls, and auditability
 * A strong track record of institutionalizing governance frameworks through standards, automation, and contractual mechanisms
 * Excellent stakeholder-management skills, with the ability to align business, engineering, and risk/compliance teams around pragmatic solutions
 * Experience improving data quality and operational reliability at scale across multiple systems and business domains as well as fluency in English; additional languages are an advantage

## Description

As Head of Data, you own the enterprise data foundation required to make AI and digital roadmaps executable. You lead the AI&E's Data pillar, overseeing the integrated data layer, semantic and knowledge graph capabilities, and the governance frameworks that ensure data is reliable, secure, and compliant. Your day balances strategic decision-making, operational oversight, and collaboration within AI&E, GS D, and other business teams to ensure every initiative starts with trusted, validated data.
How You'll Make an Impact

 * Build, operate, and continuously improve enterprise data products and the underlying data platform, including DataOps pipelines
 * Drive data readiness for roadmap initiatives confirming feasibility, availability, and prerequisites to ensure on-time delivery
 * Own and enforce data contracts, including schema definitions, freshness SLAs, quality checks, and access controls
 * Implement governance guardrails such as data classification, DLP controls, audit logging, lineage, and retention processes working in collaboration with GS D counterpart.
 * Establish automated data quality monitoring and scalable remediation pathways to prevent data issues from blocking AI delivery
 * Partner closely with in AI&E, GS D and business stakeholders to ensure initiatives scale safely with trusted data and clear ownership