Head of Data Platform in Zürich

Overview

In this role you will lead the enterprise data platform strategy and execution at SCOR, shaping a Databricks- and Palantir Foundry–driven ecosystem that enables data, analytics, and AI at scale. You will own architecture, governance, cost control, and platform excellence, aligning with SCOR’s risk-driven mission. You’ll drive innovation in agentic AI workflows while ensuring secure, compliant, and scalable delivery of data products and AI use cases. Collaborating with senior stakeholders, you enable self-service analytics and business-driven data solutions that accelerate growth and AI adoption.

Verantwortungsbereiche

• Define and own the enterprise data platform vision and roadmap across Databricks and Palantir Foundry
• Oversee end-to-end platform architecture including ingestion, transformation, storage, analytics, and AI enablement
• Build and lead a Data Platform Center of Excellence to drive adoption and enablement
• Establish and enforce governance, security, and regulatory compliance across the platform
• Manage platform FinOps and cost optimization for data and AI workloads
• Define reference architectures, patterns, and data products; ensure observability and operational excellence
• Lead and grow a global team of platform engineers, architects, governance and FinOps professionals
• Collaborate with executive stakeholders to align platform investments with business priorities

Zentrale Anforderungen

• +8 years in platform management or architecture with management experience
• Proven experience leading enterprise data platforms at scale
• Strong experience with Databricks and/or Palantir Foundry (incl. governance, platform ops, and architecture)
• Experience in financial services, insurance, or other regulated industries is a strong plus
• Deep expertise in modern data platforms (Databricks Lakehouse, Palantir Foundry, cloud ecosystems)
• Strong knowledge of distributed data processing (Spark, PySpark, SQL)
• Expertise in data governance, metadata management, lineage, and data modeling
• Experience with AI/ML platforms and AI-driven architecture
• Proven ability to enforce enterprise-wide data platform standards and scalable usage
• Strong FinOps understanding and cost optimization for data platforms
• Experience with CI/CD, DevOps, and infrastructure-as-code
• Familiarity with APIs, integration patterns, and data contracts
• Strong leadership and stakeholder management at executive level
• Ability to drive cultural transformation toward data and AI adoption

• Strategic thinking
• Executive-level stakeholder management
• Ownership mindset
• Databricks Lakehouse
• Palantir Foundry (incl. AIP)
• Spark/PySpark/SQL