Lead Data Engineer – Finance

Overview

In this role you drive data engineering for the Finance domain within the Tech, Data & AI team. You own end-to-end Finance data pipelines, ensuring robust, scalable, and governance-compliant datasets for financial reporting and IFRS 17 processes. You lead by example, mentoring engineers and shaping SCOR's data engineering practices, including AI-ready platforms. You collaborate with finance, actuarial, risk, and data stakeholders to deliver impactful analytics and regulatory-aligned solutions.

Verantwortungsbereiche

• Lead data engineering activities within the Finance domain and plan work aligned with priorities and regulatory timelines
• Own end-to-end Finance data pipelines from ingestion to consumption with reliability, scalability, auditability, and cost efficiency
• Provide hands-on technical leadership by reviewing pipelines and enforcing engineering best practices
• Design and optimize large-scale data processing solutions for Finance use cases (reconciliation, granularity, performance, traceability)
• Maintain architectural ownership of Finance data pipelines and datasets with clear documentation (code, lineage, data definitions, release notes)
• Ensure data quality, consistency, and governance across Finance datasets with internal controls and regulatory expectations
• Coach and mentor data engineers to develop skills, autonomy, and engineering excellence
• Collaborate with Finance, actuarial, risk, data and AI stakeholders through workshops and agile ceremonies
• Contribute to evolving data engineering practices, especially AI-ready data platforms and finance analytics

Zentrale Anforderungen

• 7+ years as Data Engineer with data-centric mindset
• 3+ years in a technical leadership role
• Proven track record delivering production-grade data pipelines in agile environments
• Experience with Palantir Foundry and/or Databricks
• Finance domain experience in (Re)insurance or financial services is a strong plus
• Strong hands-on Python, PySpark, and SQL
• Solid understanding of data processing (CDC, SCD) and data modeling
• Experience with CI/CD pipelines, Git workflows, and production best practices
• Good knowledge of REST APIs
• Software engineering mindset with data focus
• Excellent communication and stakeholder engagement skills
• Proven ability to lead and mentor teams in a matrix, international environment

• Strong communication with senior stakeholders
• Curiosity and willingness to learn the insurance/reinsurance business
• Analytical thinking and structured problem solving
• Python
• PySpark
• SQL