Head of Data Platform

Within our Tech, Data & AI organization, we are seeking a Head of Data Platforms to lead the design, operation, and continuous evolution of SCOR's enterprise data platform ecosystem, centered around Databricks and Palantir Foundry. This role is for a senior leader who combines deep platform expertise, strong engineering leadership, and forward-looking innovation, especially in the agentic AI space. You will own the platforms that enable data, analytics, and AI at scale, ensuring they are trusted, governed, cost-efficient, and continuously scaling business growth and AI adoption.

Under the responsibility of the Head of Data Platform, your mission will be to:

1. Platform Strategy & Ownership

• Define and execute the enterprise data platform vision, architecture, and roadmap across Databricks and Palantir Foundry, aligned with SCOR's business and AI strategy
• Own the end-to-end platform architecture, including ingestion, transformation, storage, analytics, and AI enablement layers
• Ensure the data platform scales in line with business growth, increased data volumes, and expanding AI use cases, while maintaining performance, resilience, and cost efficiency
• Lead the modernization and consolidation of legacy data systems into a unified, scalable platform ecosystem

2. Platform Enablement & Adoption

• Build and lead a Data Platform Center of Excellence (CoE) to drive adoption, onboarding, and enablement
• Support business to empower self-service analytics and AI
• Act as a strategic partner to business and domain teams to prioritize, industrialize, and scale high-value use cases in line with platform capacity and business demand

3. Governance, Security & Compliance

• Establish and enforce enterprise-wide governance frameworks covering access control, and regulatory compliance
• Define and operate platform governance models
• Ensure alignment with regulatory requirements (e.g. data privacy, auditability, AI governance)

4. Cost Management & FinOps

• Own platform cost management (FinOps) across data and AI workloads, ensuring transparency, accountability, and optimization
• Implement cost control mechanisms
• Drive a culture where cost efficiency is embedded into engineering and data usage practices

5. Excellence & Best Practices

• Lead the definition of reference architectures, reusable patterns, and canonical datasets / data products
• Establish platform observability, monitoring, and operational excellence practices

6. Leadership & Stakeholder Management

• Lead and grow a high-performing global team (platform engineers, architects, governance, FinOps)
• Collaborate with executive stakeholders to align platform investments with business priorities.
• Act as the enterprise authority on data platforms, advising on strategy, innovation, and risk.

• 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 define, implement, and enforce enterprise-wide data platform standards, ensuring consistent engineering practices, data models, governance policies, and scalable usage across the organization
• Strong understanding of FinOps principles and cost optimization for data platforms
• Experience with CI/CD, DevOps, and infrastructure-as-code
• Familiarity with APIs, integration patterns, and data contracts

• Proven experience scaling data platforms in line with business growth, increasing data volumes, and expanding AI workloads, while continuously optimizing performance, cost efficiency, and resource utilization
• Strategic thinker with strong execution capability
• Entrepreneurial mindset and strong sense of ownership
• Ability to balance innovation (AI) with governance and risk management
• Excellent stakeholder management at executive level
• Strong leadership and people development capabilities
• Ability to drive cultural transformation toward data and AI adoption