Job Description

Data is at the core of SCOR's strategic plan Forward 2026 as one of its key enablers. The Chief Data Officer organization plays a central role in delivering a governed, trusted data platform acting as a Single Version of Truth across the organization.

As Head of Data Engineering, you are accountable for the end-to-end data integration, ensuring that data is correctly extracted, transformed, and delivered from operational systems into analytical and AI platforms.

Your primary responsibility is to design and operate scalable data pipelines (batch, real-time, streaming) that ensure consistent, high-quality data flows across the enterprise. You ensure strong alignment between business logic, technical implementation, and system interoperability, enabling reliable and governed data delivery.

A key part of the role is to work upstream with business and IT teams to improve data quality at source, embedding controls, ownership, and governance into operational processes and systems.

You lead cross-functional engineering teams across the Property & Casualty, Life & Health, Finance, and Risk domain, and operate in an agile, product-based delivery model, ensuring that data integration capabilities continuously evolve to meet business needs. In parallel, you drive the evolution of data engineering practices by integrating agentic AI capabilities, automating pipeline development, monitoring, and optimization to increase delivery velocity and reliability.

Responsibilities

Key duties and responsibilities

Design and implement robust, scalable, and reusable data integration pipelines (batch, real-time, streaming) to serve enterprise analytics and AI use cases
Drive engineering excellence by enforcing best practices to ensure reliable, scalable, and high-performance data pipelines
Bridge business logic, technical semantics, and system interoperability to enable consistent and governed data delivery
Provision clean, structured, and contextualized data to support analytics products, dashboards, and AI initiatives
Ensure alignment with analytical data models, semantic layers, and data product definitions across domains
Collaborate with business and IT teams to identify and resolve data quality issues at source and embed data quality requirements into system evolution
Translate business and analytical requirements into scalable technical integration designs
Define and enforce best practices, frameworks, and standards for data engineering and integration
Ensure high performance and scalability of pipelines through monitoring of latency, data freshness, and reliability
Define and track KPIs and SLAs (e.g. uptime, delivery performance) to ensure operational excellence
Lead and develop cross-functional engineering teams, driving agile delivery and clear prioritization aligned to business impact
Drive the transformation of data engineering by leveraging agentic AI, enabling AI-assisted pipeline development and testing and alike

Qualifications

Required experience & competencies

Extensive hands-on experience in data engineering
4+ years in a leadership role, with proven ability to lead engineering teams or large cross functional initiatives and influence senior stakeholders
Demonstrates an entrepreneurial mindset with a strong sense of ownership, taking accountability for delivering high impact data engineering solutions end to end
Strong track record in designing and delivering large-scale data pipelines and integration architectures across the full data lifecycle
Strong expertise in modern data platforms such as Databricks, Palantir Foundry, including batch, real time, and streaming data architectures
Proven ability to ensure high data quality and reliability across pipelines, including influencing upstream systems and processes
Strong experience in optimizing Spark workloads through effective partitioning, caching, and query performance tuning
Solid understanding of data governance, lineage, and data management frameworks in an enterprise environment
Experience working in agile delivery models with a focus on prioritization, scalability, and continuous value delivery
Strong communication and stakeholder management skills with the ability to bridge business and technology
Experience applying AI driven automation or strong ability to drive the adoption of agentic AI to transform data engineering practices
Experience in insurance or reinsurance business processes is a strong advantage
Strong analytical and problem-solving skills with a focus on root cause analysis
Excellent organizational skills and a structured, objective driven mindset
Strong commitment to quality and client orientation
Proficiency in English; French is a plus
Willingness to travel

Required Education

Degree in a technical discipline (software engineering, engineering, mathematics, physics) or management with relevant technical expertise.

About Us

As a leading global reinsurer, SCOR offers its clients a diversified and innovative range of reinsurance and insurance solutions and services to control and manage risk. Applying "The Art & Science of Risk," SCOR uses its industry-recognized expertise and cutting-edge financial solutions to serve its clients and contribute to the welfare and resilience of society in around 160 countries worldwide.

Working at SCOR means engaging with some of the best minds in the industry - actuaries, data scientists, underwriters, risk modelers, engineers, and many others - as we work together to find solutions to pressing challenges facing societies.

As an international company, our common culture is defined by "The SCOR Way." Serving both to build momentum that drives the Group forward and as a compass to guide our actions and choices, The SCOR Way is anchored by five core values, reflecting the input of employees at all levels of the Group. We care about clients, people, and societies. We perform with integrity. We act with courage. We encourage open minds. And we thrive through collaboration.

SCOR supports inclusion and the diversity of talents, and all positions are open to people with disabilities.

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