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.
ResponsibilitiesData 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.
Technical Skills:
- 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.
- Strong collaboration skills within multicultural and distributed teams.
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
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.
Skills Required
- 7+ years of experience in Data Engineering or Software Engineering
- Strong expertise in Databricks
- Strong expertise in Apache Spark and PySpark
- Strong expertise in Python
- Strong expertise in SQL
- Experience designing and implementing enterprise data pipelines
- Strong understanding of Delta Lake
- Strong understanding of data modeling
- Strong understanding of data quality
- Strong understanding of metadata management
- Strong understanding of data governance
- Experience integrating data platforms with Java and Spring Boot applications
- Knowledge of REST APIs and microservices architectures
- Experience with Git and CI/CD practices
- Strong analytical and problem-solving abilities
- Excellent communication and stakeholder management skills
- Ability to lead technical discussions and influence architecture decisions
- Ability to collaborate within multicultural and distributed teams
What We Do
SCOR, one of the world’s largest reinsurers, serves more than 5,000 clients worldwide, providing a diversified and innovative range of solutions to control and manage risk. SCOR delivers advanced financial solutions, analytics and services across all dimensions of risk in Life & Health, Property & Casualty, and Investments. Reinsurance lies at the intersection of technical expertise and scientific progress. Models, data, and pricing and reserving tools are essential, yet they are never sufficient on their own. Sound risk decisions require expert judgment, experience and perspective. This is what we call the Art and Science of Risk. Reinsurance is a knowledge industry, where expertise grows through accumulation, transmission and practice. Across the Group, 3,600 experts based in more than 35 offices worldwide contribute to this collective intelligence. Actuaries, underwriters, risk management specialists, and Tech & Data experts transform data into insight, explore extreme scenarios, define the boundaries of insurability and help anticipate emerging risks. Together, they strengthen the resilience of SCOR, our clients and the societies we serve. This expertise is built through shared experience,continuous questioning and collective reflection. Like artists, we belong to schools of thought, learning first to observe, then to replicate, and ultimately to innovate. This ongoing transmission of knowledge enables SCOR to develop a distinctive approach, combining rigor, creativity and long-term vision in the service of risk mastery. This shared commitment underpins SCOR’s role as a global reinsurer. By turning risk into resilience and sustainable value, our collective of experts acts with responsibility and purpose. Together, we help protect the future, and shape it, for our clients, for society and for generations to come.
