Head of Data Platform

SCOR Global Life Zürich, Zurich – Suisse Publié le 25/09/2026
Description du poste
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
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