Lead Data Engineer

Our client is a global reinsurance company that combines expertise in risk with data and technology to help build more resilient societies. Within its Tech, Data & AI organization, the company is looking for a Lead Data Engineer to lead data engineering activities supporting corporate functions such as HR and Procurement.

The role combines hands-on technical expertise with team leadership and contributes to the development of data platforms that support analytics and future AI applications.

Job Summary

We are seeking a Lead Data Engineer for the Corporate Data domain to join our Tech, Data & AI team. The successful candidate is a hands-on technical leader with deep data engineering expertise, strong communication skills, and a solid understanding of corporate data domains and processes in a complex environment such as reinsurance.

You will be responsible for leading data engineering activities for Corporate Data, ensuring the robustness, scalability, and quality of data pipelines and analytical datasets supporting corporate functions and enterprise-wide reporting. Beyond delivery, you will help shape how data engineering evolves at SCOR, including its role in enabling AI driven use cases and self-service analytics.

This position is not a generic software engineering role: it requires strong ownership of data flows, data models, and analytics ready datasets that directly support corporate reporting, group-level KPIs, management decision making, and regulatory requirements. Key duties and responsibilities

1. Lead data engineering activities within the Data Foundation of the Group Function Data domain, supervising, coordinating, and planning your team’s work in line with business priorities across Group Functions.
2. Own end to end Group Functions Data pipelines, from ingestion to consumption, ensuring reliability, scalability, and cost-efficient performance.
3. Provide hands on technical leadership by reviewing data pipelines and data services, enforcing state of the art engineering practices.
4. Design and optimize large scale data processing solutions supporting corporate use cases, addressing challenges such as data integration, harmonization, and cross-domain consistency.
5. Maintain architectural ownership of corporate data pipelines and datasets, enforcing clear documentation including code, lineage, data definitions, and release notes.
6. Ensure data quality, consistency, and governance across Group Functions Data datasets.
7. Coach and mentor data engineers, supporting skill development, autonomy, and a culture of engineering excellence.
8. Collaborate closely with business stakeholders across HR, Legal, Procurement, and other group functions, as well as Data Foundation, Governance, and Platform teams.
9. Contribute to the definition and evolution of enterprise data standards, models, and engineering best practices.
10. Actively contribute to the evolution of data engineering practices, particularly in the context of AI ready data platforms and self-service analytics. Required experience & competencies +7 years of experience as a Data Engineer with a strong data-centric mindset +3 years of experience in a technical leadership role Proven track record delivering and operating production-grade data pipelines in an agile environment Proven experience with Palantir Foundry and / or Databricks is a strong plus Experience in (Re)insurance, financial Services, or other complex data-intensive industries is a strong plus Technical Skills: Strong hands-on expertise in Python, Py. Spark and SQL. Proven experience with Databricks and/or Palantir Foundry (strongly preferred). Solid understanding of distributing data processing, CDC, slowly changing dimensions, and data modeling. Srong exposure to CI / CD pipelines, Gitflows, and production best practices. Good knowledge of REST API Behavioral & Management Skills: Software engineering first mindset with solid experience in data. Curiosity and interest in learning the insurance/reinsurance business. Strong analytical thinking, structure problem solving, and ownership attitude. Excellent communication skills, with the ability to engage senior business and technical stakeholders. Proven ability to lead, mentor, and inspire teams in a matrix, international environment.