Head of Data Platform

At SCOR we combine the Art and Science of risk to help build more resilient societies. Data and AI are at the heart of this ambition.

Within our Tech Data & AI organization we are seeking a Head of Data Platforms to lead the design operation and continuous evolution of SCORs 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.

You will play a critical role in shaping how SCOR leverages modern data platforms such as Databricks and Palantir Foundry (incl. AIP) to deliver high-impact business outcomes across underwriting pricing reserving and corporate functions.

You will define and own the platform strategy governance model operating model and engineering standards ensuring that the platform enables scalable data products AI use cases and self-service analytics.

Beyond platform stability and delivery you will drive innovation in the agentic AI space enabling new ways of working through AI-powered workflows automation and decision intelligence. This role requires a strong balance between strategy architecture governance and hands-on leadership with a particular focus on:

• Architecture governance and compliance (data AI access regulatory)
• Cost management (FinOps for data and AI platforms)
• Platform standards adoption and best practices
• Enabling business-driven use cases at scale

Key duties and responsibilities

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 SCORs 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.

Required experience & competencies

• 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

Required Education:

• BSc in computer or data science software or computer engineering applied math physics statistics or a related field or equivalent experience

Technical Skills:

• 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

Behavioral & Management Skills:

• 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