Lead Data Engineer

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

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

• 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.

• Own end to end Group Functions Data pipelines, from ingestion to consumption, ensuring reliability, scalability, and cost-efficient performance.

• Provide hands on technical leadership by reviewing data pipelines and data services, enforcing state of the art engineering practices.

• Design and optimize large scale data processing solutions supporting corporate use cases, addressing challenges such as data integration, harmonization, and cross-domain consistency.

• Maintain architectural ownership of corporate data pipelines and datasets, enforcing clear documentation including code, lineage, data definitions, and release notes.

• Ensure data quality, consistency, and governance across Group Functions Data datasets, contributing to SCOR’s Single Version of Truth and federated governance model.

• Coach and mentor data engineers, supporting skill development, autonomy, and a culture of engineering excellence.

• Collaborate closely with business stakeholders across HR, Legal, Procurement, and other group functions, as well as Data Foundation, Governance, and Platform teams.

• Contribute to the definition and evolution of enterprise data standards, models, and engineering best practices.

• 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, PySpark 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.

• Strong 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.

Required Education

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