Referential Service Lead

SCOR is seeking a Referential Service Lead to lead the strategy, governance, delivery, and continuous improvement of SRDS (SCOR Reference Data Service) application and other enterprise referential applications.

The role owns the Referential Service capability end to end, ensuring that key reference data domains, golden sources, data quality rules, lifecycle management, and integration patterns are consistently defined, governed, and operated across consuming applications.

As SCOR strengthens its data foundation and modernizes business applications, this leader will ensure that referential data is governed, reliable, reusable, auditable, and fit for purpose across domains, tools, and processes.

The position acts as the primary technology partner for business and data stakeholders on referential data needs, ensuring alignment with enterprise architecture, data governance, security, integration standards, and product delivery practices.

The Head of Referential Service will coordinate multidisciplinary contributors across product, engineering, architecture, data governance, operations, and business domains to deliver trusted referential services and drive adoption across SCOR.

Beyond service ownership and delivery coordination, the role is expected to provide strong engineering leadership, challenge technical decisions, promote modern software engineering practices, and ensure that referential platforms are scalable, secure, maintainable, observable, and resilient by design.

Referential Service Strategy and Ownership

• Define and maintain the strategy, roadmap, and operating model for the Referential Service, including SRDS and other referential applications.
• Own the service vision for enterprise reference data, ensuring consistency, reuse, scalability, operational reliability, and measurable business value.
• Prioritize service backlog items, MVP scope, enhancements, run activities, and technical debt remediation in collaboration with business and IT stakeholders.
• Ensure referential applications support critical domains such as Life & Heath, P&C, Finance and others.

Business Engagement and Data Governance

• Act as the main point of contact for business stakeholders requiring new or improved referential data capabilities.
• Translate business needs into clear functional requirements, data models, governance rules, and delivery priorities.
• Promote ownership, stewardship, data quality controls, approval workflows, auditability, and lifecycle management for reference data.
• Challenge fragmented local referential and drive convergence toward trusted enterprise sources.

Engineering Leadership and Technical Excellence in collaboration with de Domain Lead

• Lead engineering practices across referential applications, ensuring robust solution design, maintainable code, scalable integration patterns, and reliable production operations.
• Challenge technical decisions and contribute hands-on to architecture reviews, API design, data model definition, troubleshooting, and complex delivery topics when required.
• Promote software engineering best practices, including code quality, testing strategy, CI/CD, DevSecOps, observability, documentation, and technical debt management.
• Ensure non-functional requirements such as performance, security, resilience, auditability, maintainability, and supportability are properly addressed from design to production.

Service Delivery and Integration Leadership

• Lead end-to-end delivery of SRDS features, referential service enhancements, and operational improvements from discovery to production adoption.
• Coordinate solution design across data modeling, APIs, user interfaces, workflows, permissions, audit trails, and operational support.
• Ensure smooth integration with consuming applications, data platforms, analytics products, and enterprise services.
• Drive release planning, user acceptance testing, change management, documentation, service onboarding, and run support readiness.
• Remain hands-on when needed by actively contributing to analysis, solution design, backlog refinement, testing, troubleshooting, and delivery activities.

Technology Modernization and Innovation

• Evaluate alternative solutions leveraging: 
  • AI Workbench capabilities
  • Agentic AI platforms
  • Data Foundation services
  • Analytics and Data products
  • Domain-owned workflow and orchestration capabilities
• Drive innovation initiatives designed to improve productivity and operational efficiency.
• Ensure new solutions are aligned with enterprise architecture principles and strategic technology standards.

Leadership and Delivery Management

• Lead and develop developers and specialists located across multiple delivery centers. 
• Establish objectives, priorities, performance expectations, and development plans.
• Drive delivery excellence across support, maintenance, enhancement, and transformation initiatives.
• Foster strong collaboration across business, engineering, architecture, AI, and data organizations.

Governance and Risk Management

• Define and monitor KPIs related to automation value realization, efficiency gains, platform usage, and portfolio health.
• Ensure compliance with security, operational resilience, architecture, and regulatory requirements.
• Contribute to IT strategy, investment decisions, and technology governance forums.

• 8+ years of experience in enterprise technology, data management, master/reference data, application delivery, or digital transformation domains.
• Proven experience delivering referential, master data, or data governance solutions in complex organizations.
• Strong experience with software engineering practices, data modeling, APIs, application integration, cloud or enterprise data platforms, workflow-enabled governance, and product delivery practices.
• Proven ability to work closely with developers, architects, platform teams, and operations to review solution designs, address technical constraints, and drive engineering-quality delivery.
• Demonstrated experience coordinating multidisciplinary teams, vendors, business stakeholders, data owners, and technology partners.
• Strong track record in application modernization, data quality improvement, referential convergence, and enterprise data transformation programs.
• Experience working with business stakeholders and cross-functional leadership teams.
• Leadership
• Strategic thinker capable of connecting technology decisions to business outcomes.
• Strong influencing and stakeholder management capabilities.
• Ability to challenge established practices constructively and drive change. 
• Reference data and master data management principles
• Data governance, stewardship, quality controls, and lifecycle management
• Data modeling, APIs, application integration, and enterprise data platforms
• Agile product delivery, backlog management, MVP definition, and release planning
• Software engineering practices, including CI/CD, DevSecOps, automated testing, code quality, observability, documentation, and technical debt management
• Enterprise architecture principles, security, auditability, and operational resilience
• Knowledge of insurance or reinsurance data domains is a plus
• Degree in Computer Science, Management of Information Systems, or a related analytical field; or equivalent experience.