Description
The Data Engineer is responsible for designing, building, and maintaining data pipelines and systems that support actuarial modelling, pricing, reserving, and risk analytics.
The role bridges Actuarial Science and Data Engineering by ensuring actuarial models receive accurate, structured, and high-quality data.
Additionally, support reporting through dashboarding.
Core Responsibilities
Data management and processing
- Collect, clean, and validate data
- Design and maintain ETL pipelines for actuarial datasets
- Support data models for health data (policies, claims, exposures)
- Integrate multiple data sources into actuarial data marts
- Engaging with client IT/data teams
Actuarial Data Support
- Prepare data for actuarial modelling and reporting
- Automated validation
- Consistency of data between source and analytical platform
- Documentation
Dashboard development
- Design and maintain interactive dashboards using Tableau, Power BI, etc.
- Reporting: Generate reports and dashboards to communicate findings.
Technical competencies and skills required
- Proficiency in programming – Python, SQL, R, etc.
- Proficiency in business intelligence tools - Tableau, Power BI etc
- Working knowledge and understanding of data platforms SQL Server, Postgres, Databricks or other cloud solutions (AWS, Azure)
- Hands-on experience with ETL tools and data integration processes
- Health insurance data, insurance, reserving, pricing models
- Strong analytical and communication skills, collaboration with actuarial and clinical team members.
Qualifications:
- Degree in Computer Science, Software Engineering, Actuarial Science
- Data Science, Statistics, or related field (analytical field with good conceptual awareness of financial or health insurance data analysis is required where not an actuarial degree).
- 3-5 Years of Experience