Head Corporate Data & Analytics

About the role

Syngenta's Enterprise Application Team is looking for a Head Corporate Data & Analytics to own and lead the Corporate Function Enterprise Data Hub within the Databricks Data Mesh. The role delivers business value through data products, analytics, machine learning and AI solutions, leads the migration of legacy data products into the enterprise data mesh, and builds and leads a multidisciplinary data team. The posting is listed under Madrid.

Key responsibilities

• Lead the strategy, roadmap, operating model and day-to-day performance of the Corporate Function Enterprise Data Hub, aligned to Enterprise Data Mesh architecture, governance and platform standards.
• Own end-to-end delivery and lifecycle management of corporate function data products so they are discoverable, reliable, secure, reusable and fit for business consumption.
• Lead analytics, machine learning and AI solutions from use-case shaping through adoption and value realisation.
• Drive the structured migration, rationalisation and retirement of legacy data products into the Databricks Data Mesh, balancing business continuity, risk and technical debt reduction.
• Build, coach and lead a team of data analysts, data engineers, ML engineers and AI engineers, with clear accountabilities and capability development.
• Partner with Corporate Function leadership, GSS and IT Business Partnering to prioritise demand, define product value, manage trade-offs and secure adoption.
• Ensure compliance with enterprise data governance, security, privacy, quality, risk and responsible-AI requirements.
• Manage the data hub's capacity, supplier engagement and investment, and report delivery performance, risks, dependencies and value to senior stakeholders.

Required profile

• Bachelor's degree or equivalent experience in computer science, data science, engineering, information systems, mathematics or a related discipline; advanced degree is advantageous.
• Deep knowledge of data architecture, data engineering, analytics, data-product management, cloud platforms and the lifecycle of ML and AI solutions.
• Strong commercial and business acumen, able to explain complex technical matters to senior non-technical stakeholders.
• Professional fluency in English.
• Desired: 10+ years of relevant experience in data, analytics, data engineering, AI/ML, digital product delivery or technology leadership, including leading multidisciplinary teams.
• Desired: experience modernising legacy data and analytics estates, and working across global Corporate Functions, shared services and IT business partnering environments.

Required skills

• Working knowledge of Databricks and modern data mesh concepts.
• Data governance, metadata, data quality, security and privacy controls, and responsible-AI principles.
• Preferred: experience delivering enterprise-scale data products on modern cloud data platforms, preferably Databricks, and migrating legacy estates.