Lead Data Engineer
Fa Errt Saasfaprod1 Open · verified Oct 24, 2026 At a glance
Senior Data Engineering role at Fa Errt Saasfaprod1. Bucuresti - Ilfov, Romania.
Pay not stated Lead Data Engineer salary
dataroles summary, based on the employer's posting.
What you'll do
- Lead Group Functions data engineering work, planning the team’s activities around business priorities
- Own data pipelines from ingestion through use, keeping them dependable, scalable and cost-efficient
- Review pipelines and data services, setting engineering practices through hands-on technical guidance
- Build large-scale data processing for corporate needs, addressing integration and consistency across domains
- Document pipeline architecture and datasets, uphold data quality and governance, and mentor engineers
What you bring
- At least seven years working as a data engineer with a strong data-focused approach
- At least three years in technical leadership and a record of running production pipelines in agile teams
- Strong working knowledge of Python, PySpark and SQL, plus distributed processing, CDC, data modeling and REST APIs
- A degree in computing, quantitative studies or a related field, or equivalent experience
Who this fits
This suits a hands-on technical lead who can guide engineers while owning corporate data pipelines, models and reporting datasets. You’ll work with stakeholders across group functions and data teams in an international, matrix environment. Curiosity about insurance or reinsurance is valued.
From the employer
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
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