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Bucuresti - Ilfov, Romania
Actively hiring, first seen by us 4 days agoOwn end-to-end Group Functions data pipelines, from ingestion to consumption
Review data pipelines and services and enforce engineering standards
Design and optimize large-scale data processing for corporate use cases
Maintain documentation for code, lineage, data definitions and release notes
Coach and mentor data engineers
Own end to end Group Functions Data pipelines, from ingestion to consumption
Provide hands on technical leadership by reviewing data pipelines and data services
Design and optimize large scale data processing solutions supporting corporate use cases
enforcing clear documentation including code, lineage, data definitions, and release notes
Coach and mentor data engineers
Solid understanding of distributing data processing, CDC, slowly changing dimensions, and data modeling.
Excellent communication skills, with the ability to engage senior business and technical stakeholders.
Good knowledge of REST API
Proven ability to lead, mentor, and inspire teams in a matrix, international environment.
Proven experience with Databricks and/or Palantir Foundry (strongly preferred).
Actively hiringFirst seen by us 4 days ago, still listed, and not a repost of an earlier posting.
These dates show when we found the posting. Check the employer’s website to confirm it is still accepting applications.
Day 4
Early. Similar jobs usually come down between day 5 and day 54.
From 12,144 similar postings that came down. Coming down is not always a hire.
23 open jobs
Open jobs by the week we first saw them, last 12 weeks.
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Technical Skills: - Strong hands-on expertise in Python, PySpark and SQL. - Proven experience with Databricks and/or Palantir Foundry (strongly preferred).
- 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
- 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.
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New Data Engineer postings at the employers we follow are up 7% over the last 6 weeks compared with the 6 before.
Each bar is one week of new postings. The darkest bars are the last 6 weeks.
Counted from the hiring pages we’ve followed for at least five weeks, so employers we add don’t look like growth. Updated weekly.
We file this job under Data Engineer, by the work the posting describes.
Data engineers build and run the pipelines that copy data out of apps and outside services into a warehouse or lake, and fix them when a source changes or a load fails.
Expect SQL, Python, a cloud platform, a scheduler such as Airflow, and often tools for large data such as Spark or Kafka.
An analytics engineer works one step later, turning the raw data a data engineer lands into clean tables people can query.
The government has no code for data engineers, so these figures are for the closest group, database architects, which includes data integration and data warehousing specialists.
Source: US Bureau of Labor Statistics, Occupational Employment and Wage Statistics (May 2025) and Employment Projections (2025 to 2035). Occupation code 15-1243.
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
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Bucuresti - Ilfov, Romania
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