Description
People & Culture Data and AI Lead
Job Summary
The People & Culture Data and AI Lead owns the end-to-end delivery of P&C data products — from source systems into governed, analytics-ready datasets and semantic models — and delivers global data, data science, and advanced analytics to senior P&C leaders, the Executive Committee, and the Board. The role ensures employee data is trusted, protected, governed, and used appropriately across the organisation.
Key Accountabilities
1. Lead technical delivery of P&C datasets from source systems (. IFS) into Fabric/Azure/Synapse across landing, curated, and semantic layers; produce implementation-ready specifications for engineers and modellers.
2. Own the P&C certified semantic layer design including measures, calculations, and role-based access; define, document, and validate P&C metrics including headcount, attrition, absence, recruitment, diversity, and workforce planning.
3. Implement data quality controls in Azure and Purview; define reconciliation routes to operational reports and own the certified report suite.
4. Deliver AI-enabled analytics, automation and data science; validate AI-generated P&C insights for accuracy, fairness, sensitivity, and explainability; define appropriate AI self-service use cases and ensure AI tools operate only on approved, access-controlled data.
5. Ensure P&C data is governed with appropriate sensitivity, privacy, and ethical controls; work with the Data and AI Governance Lead to classify data and manage personal and sensitive workforce data risks.
6. Lead UAT, business validation, and sign-off for P&C analytics, semantic models, and AI outputs; support stakeholders in transitioning from manual reporting to governed, AI-enabled workforce analytics.
Skills and Competencies
7. Expertise in semantic data modelling (physical, dimensional, logical) and enterprise architecture.
8. Advanced hands-on skills in Microsoft Azure and modern data lakehouse tooling for reporting, automation, data development and analysis.
9. Working knowledge of data science, AI, and machine learning in analytics, including responsible use controls.
10. Strong understanding and skills in of AI risks: privacy, fairness, explainability, and inappropriate automated decision-making.
11. Metric definition, workforce analytics, and people data interpretation.
12. Strong data visualisation and UX skills; UAT, reconciliation, and business validation capability.
13. Delivery of automation and advanced analytics and quality data products, including integrating multiple source systems.
Qualifications and Experience
Essential
14. Bachelor's degree in data analytics, data science, or a related discipline.
15. Extensive experience in data, AI and analytics delivering secure, high-value, executive-level certified data with measurable business impact.
16. Extensive experience implementing Microsoft Azure and self-service data and AI platform frameworks at scale.
17. Strong background in analytics, AI/M and reporting; experience handling sensitive employee data, privacy requirements, and access controls.
18. Experience working with data engineers, architects, and business domain leads; prior experience in a technical data team with a CDO.
19. Experience with data standardisation frameworks for harmonising definitions, taxonomies, and formats across regions.
20. Experience with Power BI, SQL, semantic models and governed reporting platforms.
21. Experience with AI-enabled analytics, responsible AI.
Desirable
22. Experience with HR platforms such as Workday or equivalent.
23. Experience working with privacy, legal, or HR leadership on sensitive workforce data.
24. Relevant certifications in HR, people analytics, data, Power BI, SQL, privacy, Microsoft, or AI analytics.