Más empleos:
Director, People Data & Analytics Human Resources
Trabajo disponible en:
08001, Barcelona, Cataluna, España
Publicado en 2026-07-31
Empresa:
Bacardi-Martini
Tiempo completo
puesto Publicado en 2026-07-31
Especializaciones laborales:
-
TI/Tecnología
Analista de datos, Tecnologia de Negocios, Seguridad de la Información, Gerente de Ciencias de Datos
Descripción del trabajo
The Director, People Data & Analytics will define and lead the global People Analytics strategy, transforming HR from fragmented reporting to a predictive, insight-led capability that drives measurable business impact.
This role owns the people data and analytics agenda for HR, ensuring that workforce decisions are driven by trusted data, forward-looking insights, and aligned to enterprise priorities.
Working in close partnership with the Technology Data & Analytics (D&A) function, this role will define people analytics strategy, use cases, and insights, while leveraging enterprise data platforms and capabilities delivered by Tech.
Key Responsibilities 1. Build the People Analytics Strategy Aligned to Enterprise D&A Standards- Define a multi-year People Analytics strategy aligned with enterprise D&A standards and data architecture
- Ensure HR’s people data strategy supports broader enterprise priorities such as digital transformation, supply chain optimisation, and global talent strategy.
- Create a maturity roadmap from descriptive reporting to predictive and prescriptive analytics for use cases such as attrition prediction, skills adjacency modelling, and workforce cost optimisation.
- Work with Tech D&A team to integrate external labour market data for competitive benchmarking and ensure measurable KPIs for analytics adoption and impact.
- Collaborate with the Tech/D&A governance teams to define HR’s data stewardship model and accountability framework for people data, adopting enterprise standards on; data quality, data definitions, metadata management, data access & security, privacy & compliance (including cross-border data considerations)
- Work with AI Governance forum to define and embed Responsible AI principles and bias mitigation in predictive models.
- Represent HR in enterprise data councils and lead ethical data practices.
- Partner with Tech D&A and Finance to enable integrated workforce and financial forecasting
- Ensure the right data is in place for monitoring the right KPIs, creating a single source of truth integrated with enterprise data lakes.
- Enable scalable self-service reporting and insight tools, available to all, using enterprise-standard tools (e.g., Power BI) and embed predictive insights.
- Ensure executive-ready narratives and reporting cadences aligned to business decision cycles.
- In conjunction with Tech Capability team lead change management and people analytics culture adoption across HR and business leaders.
- Co
-create a structured enablement programme for people data for HRBPs and Leaders, including certifications or learning paths in analytics literacy, data storytelling, and responsible data use.
Provide actionable insights that help Bacardi attract, develop, and engage talent for growth. Focus on:
- Deliver predictive workforce insights across the value chain, including skills forecasting, mobility analysis, diversity pipeline health, and succession risk modelling. Apply AI/ML and external market intelligence to optimise recruitment, retention, and workforce planning. Define KPIs for impact measurement.
- Translate insights into recommendations that enable Bacardi to stay competitive in the global spirits industry.
- Partner with Tech to ensure employee listening platforms integrate effectively with enterprise data architecture.
- Create a consistent approach to engagement, lifecycle surveys, pulse checks, and sentiment analysis.
- Combine qualitative and quantitative data and predictive analytics to understand culture drivers, leadership impact, and employee experience trends.
- Extensive knowledge of HR systems and data structures (Workday/SAP).
- Proven ability to build people analytics capability in low-maturity environments
- Experience with predictive modelling and machine…
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