freehire launches on Product Hunt on 26 August.

Follow →

Lead Data Engineer - Finance

Summary

Lead a team to build and maintain Finance data pipelines and datasets for a reinsurer, using Databricks and Palantir Foundry to support reporting, IFRS 17, and AI-ready analytics.

At SCOR, we combine the Art and Science of risk to help build more resilient societies. Data is at the heart of our mission. Within our Tech, Data & AI organization, we are looking for a Lead Data Engineer in Finance who lives data engineering, leads with impact, and thinks ahead to the future of data and AI.

This role is for a senior data engineering leader who owns complex Finance Data Foundation, our trusted base layer where data is collected, standardized, governed, and made ready for analytics, reporting, and AI, end to end, understands financial and reinsurance processes, and sets the bar for engineering excellence on modern data platforms such as Databricks and Palantir Foundry and alike.

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.

We are seeking a Lead Data Engineer for the Finance 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 Finance data and processes in a complex environment such as reinsurance.

You will be responsible for leading data engineering activities for the Finance domain, ensuring robustness, scalability, and quality of data pipelines and analytical datasets supporting financial and regulatory processes. Beyond delivery, you will help shape how data engineering evolves at SCOR, including its role in enabling AI driven use cases.

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 financial reporting, IFRS 17 processes, performance steering, and management decision making.

Key responsibilities:

  • Lead data engineering activities within the Finance domain, supervising, coordinating, and planning your team's work in line with Finance priorities and regulatory timelines.
  • Own end to end Finance data pipelines, from ingestion to consumption, ensuring reliability, scalability, auditability, 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 Finance use cases, addressing challenges such as reconciliation, granularity, performance, and traceability.
  • Maintain architectural ownership of Finance data pipelines and datasets, enforcing clear documentation including code, lineage, data definitions, and release notes.
  • Ensure data quality, consistency, and governance across Finance datasets, in alignment with internal controls and regulatory expectations.
  • Coach and mentor data engineers, supporting skill development, autonomy, and a culture of engineering excellence.
  • Collaborate closely with Finance, actuarial, risk, data and AI stakeholders through workshops, design sessions, and agile ceremonies.
  • Actively contribute to the evolution of data engineering practices, particularly in the context of AI ready data platforms and finance analytics.

Your profile:

  • +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
  • 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.
  • 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.

See also