APEX - Data Engineer

About Us:

At SCOR, we combine the Art and Science of risk to help build more resilient societies. Technology is a vital resource and partner in every step of our journey. We are seeking innovators to join our dynamic tech team of over 230 professionals across three global hubs. Guided by our corporate values-Collaboration, Courage, Care, Open-Mindedness, and Integrity-our teams develop technology that insures the world. Join us and make a difference!

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.

Job Summary

We are seeking a highly skilled Senior Data Engineer to join the APEX engineering team and contribute to the design, development, and evolution of our next-generation data platform.

The successful candidate will play a key role in building scalable and reliable data pipelines on Databricks, leveraging PySpark and Python to process large-scale datasets and support critical business processes. The role requires close collaboration with Backend Engineering teams to integrate data services with a Java-based ecosystem through APIs and microservices.

Data Platform Development:

• Design, develop, and maintain enterprise-grade data pipelines using PySpark on different systems as Databricks.
• Build efficient ETL/ELT processes for large-scale data ingestion, transformation, and delivery.
• Design and optimize Delta Lake data models and storage structures.
• Implement data quality controls, reconciliation mechanisms, and monitoring solutions.
• Analyze and optimize Spark workloads for performance and cost efficiency.

Backend Integration:

• Develop integrations between Databricks workloads and Java/Spring Boot applications.
• Design and consume REST APIs for data exchange between platform components.
• Support event-driven and service-oriented architectures.
• Collaborate with backend teams to ensure end-to-end data flow reliability and scalability.

Software Engineering Excellence:

• Develop reusable Python frameworks and libraries to standardize data processing.
• Apply software engineering best practices including clean code, testing, code reviews, and documentation.
• Contribute to CI/CD implementation and deployment automation.
• Participate in architecture reviews and technical design discussions.
• Strong Adoption of AI tools, AI agents and Agentic AI to bring more efficiency to deliver value. Usage of AI within databricks. Proactively propose news usage / AI tools on our technical environment being open minded.

Operational Excellence:

• Ensure reliability, observability, and supportability of production pipelines.
• Investigate and resolve performance, stability, and data consistency issues.
• Participate in production support and root cause analysis activities.
• Implement monitoring and alerting mechanisms across the data platform.

Leadership & Collaboration:

• Collaborate with architects, product owners, business analysts, and development teams.

• Contribute to technical roadmaps and platform modernization initiatives.

• 7+ years of experience in Data Engineering or Software Engineering.

• Strong expertise in:

• Databricks

• Apache Spark / PySpark

• Python

• SQL

• Proven experience designing and implementing enterprise data pipelines.

• Strong understanding of:

• Delta Lake

• Data Modeling

• Data Quality

• Metadata Management

• Data Governance

• Experience integrating data platforms with Java/Spring Boot applications.

• Solid knowledge of REST APIs and Microservices architectures.

• Experience with Git and CI/CD practices.

Soft Skills

• Strong analytical and problem-solving abilities.
• Excellent communication and stakeholder management skills.
• Ability to lead technical discussions and influence architecture decisions.
• Self-driven, proactive, and results-oriented mindset.

Technical Environment

• Data Platform: Databricks, Dataworks
• Languages: Python, PySpark, SQL, Java
• Backend: Spring Boot, REST APIs
• Cloud: Microsoft Azure, Alibaba
• Storage: Azure storage, Parquet
• DevOps: Azure DevOps, Git
• Monitoring: Grafana, ELK