2026-7854 Software Engineer (Mid Shift)

Schedule: Mid Shift

The Position:

The Software Engineer will play a critical role in the design, development, and operationalization of predictive analytics platforms and analytical applications supporting enterprise-wide insurance analytics initiatives.

This role sits within the Strategic Analytics function and is responsible not only for hands-on engineering delivery, but also for technical leadership, solution design, code quality governance, and cross-functional collaboration with data scientists, actuaries, product owners, and business stakeholders across global teams.

The position requires deep expertise in Python-based backend development, API-driven architectures, and Azure cloud services, with the ability to guide technical decisions in a fast-evolving analytics and cloud environment. The Software Engineer is expected to mentor engineers, influence architectural direction, and ensure production stability of analytics-enabled applications.

Job Responsibilities:

• Serve as a technical lead for analytics-enabled applications, APIs, and backend services supporting predictive models and analytical tools.
• Contribute to solution architecture, design standards, and best practices for scalable, cloud-native analytics platforms.
• Evaluate, recommend, and implement new technologies and frameworks aligned with Azure and analytics modernization initiatives.
• Ensure adherence to secure coding standards, performance benchmarks, and enterprise engineering guidelines.

• Design, develop, and maintain Python-based backend services supporting analytical models and data-driven applications.
• Lead the development and integration of RESTful APIs, ensuring reliability, scalability, and test coverage.
• Build and support applications leveraging Azure Functions, Azure Container Apps, Blob Storage, and Azure SQL.
• Ensure high-quality code through code reviews, unit testing, and technical documentation.

• Lead and improve CI/CD pipelines using Azure DevOps to enable automated testing, deployment, and monitoring.
• Collaborate with DevOps and platform teams to optimize cloud resource utilization, cost efficiency, and system resilience.
• Support production releases, incident response, root-cause analysis, and continuous improvement initiatives.

• Provide Level 3 application support for analytics platforms, including issue investigation, resolution, and post-incident reviews.
• Proactively identify risks and performance bottlenecks and escalate critical issues when required.
• Partner with business and analytics stakeholders to ensure solutions meet functional and operational requirements.

• Mentor and coach junior and mid-level engineers, fostering technical growth and engineering discipline.
• Work closely with data scientists, actuaries, product owners, and global technology teams to translate analytical requirements into production-ready solutions.
• Act as a technical point of contact for analytics engineering initiatives within the region.