Actuarial Data Engineer

Jobtailor; Iowa (LA); On-site; USD 100,000 - 140,000; Full time

Job summary

Jobtailor is seeking a Data Engineer to design, develop, and implement analytical data processes that support actuarial pricing, reserving, and claims analytics within a Property & Casualty insurance context.

You will build scalable data pipelines and models, partner with actuarial and finance teams, and ensure data quality and lineage across modern data warehousing and ETL environments.

Qualifications

• 3 to 6 years of data engineering experience; cloud-based data environment preferred.
• Strong proficiency in SQL, Python, or R.
• Experience building automation tools or analytical frameworks.
• Experience with modern data warehousing and ETL tools.
• Strong problem-solving skills and attention to data accuracy.

Responsibilities

• Design, develop, and implement analytical data processes for pricing, reserving, and claims analytics.
• Build and maintain scalable data pipelines, models, and tools per architecture.
• Collaborate with actuarial, data science, and finance teams to deliver structured data solutions.
• Develop and maintain analytical pipelines supporting actuarial analysis.
• Create data models providing consistent access to actuarial data.
• Support applications and tools used in pricing and analytics.
• Promote end-to-end data process best practices.
• Improve data workflows by identifying inefficiencies.
• Apply data validation, reconciliation, and quality controls.
• Maintain data lineage and documentation for transparency.
• Support experimentation with emerging AI capabilities in process flow.

Skills

SQL

Python

R

Data engineering

ETL

Tools

Data warehousing tools

Automation tools

Job description

Responsibilities

• The Data Engineer will support the design, development, and implementation of analytical data processes that enable actuarial pricing, reserving, and claims analytics across a Property & Casualty insurance business.
• This role focuses on building and maintaining scalable data pipelines, models, and tools under established architectural patterns and standards.
• The Data Engineer will partner with actuarial, data science, and finance teams to deliver reliable and well-structured data solutions that support analytical workflows and business insights.
• Develop and maintain analytical pipelines and tools that support actuarial analysis.
• Build and enhance data models that provide consistent, structured access to actuarial data.
• Support the development of applications and tools used in pricing, reserving, and claims analytics.
• Support the adoption of best practices for end-to-end analytical data process flow.
• Contribute to the continuous improvement of data workflows by identifying inefficiencies and recommending enhancements.
• Apply data validation, reconciliation checks, and quality controls within data pipelines.
• Assist in maintaining data lineage and documentation to support transparency.
• Support experimentation with emerging AI capabilities in process flow design.

Requirements

• 3 to 6 years of data engineering experience with cloud‑based data environment experience preferred.
• Strong proficiency in SQL, Python, or R.
• Experience building automation tools or analytical frameworks.
• Experience with modern data warehousing and ETL tools.
• Strong problem‑solving skills and attention to detail & data accuracy.
• Experience working with P&C insurance data preferred.
• Familiarity with actuarial data and concepts preferred.

Core Competencies

Demonstrates expertise in building and maintaining scalable data pipelines and models, with strong proficiency in SQL, Python, or R. Familiarity with actuarial data and experience in the Property & Casualty insurance domain are essential for delivering reliable data solutions.