Product Engineer

About the Team:

You will join the Global Underwriting Data & Analytics team – a talented, curious and collegial cohort committed to solving the biggest challenges facing the industry today. The team brings a deep understanding of the Underwriting problem statement and the technical purview necessary to solve it.

About the Role:

This role sits at the heart of Swiss Re’s Underwriting Analytics transformation. As a Product Engineer, you will contribute to the development, deployment, and maintenance of analytical applications that empower underwriters, actuaries, and business leaders to make fast, confident, and insight-driven decisions.
Reporting into the Head of Underwriting Analytics, you will partner closely with visualization leads, data architects, AI engineers, and product managers to build performant, scalable tooling that transforms raw data into actionable business value. Your work will span dashboards, self-service apps, and integrated ML tools—powered by the Stargate analytical data platform.
This is a hands-on role where engineering meets business impact. You'll be expected to build with precision, collaborate openly, and ensure that every line of code serves a measurable underwriting outcome. 

Strategic Mandate Alignment
Your work supports the mandate to empower the Underwriting product areas and Market Units for the future of the insurance market by delivering industry-leading capabilities.

Key outcomes include

• Data Engineering: Drive optimization and scalability through TypeScript and PySpark, enhancing data pipelines and analytical performance. 
• Visualization: Help design and maintain reporting tools that simplify access to portfolio insights and empower better decision-making.
• Advancing Analytics: Engineer and evolve plug-and-play components that scale with the growing breadth of analytical products.
• Underwriting Initiatives: Contribute to tooling used across major initiatives.

You will also support the broader transformation agenda

• Enable GenAI-powered assistants and LLM applications by ensuring analytical infrastructure is reliable, performant, and extensible.
• Embed engineering excellence that supports insight delivery at the point of quote and directly within Underwriting Workbench interfaces.

Primary Responsibilities 

A. Engineering Delivery
• Build and maintain analytical applications, dashboards, and supporting components that serve underwriters and steering teams.
• Write performant, reusable code that supports real-time, high-trust insight delivery in typescript and pyspark optimization.
• Implement version control, testing, and documentation standards for all work products.
• Integrate user feedback into the design and continuous improvement of analytical tools.

B. Collaboration & Product Execution

• Under the direction Head of Underwriting Analytics, collaborate with product managers to scope requirements and translate them into working features.
• Work closely with AI/ML engineers and data architects to ensure infrastructure compatibility and downstream usability.
• Ensure tight alignment with the Stargate data platform and adhere to shared development patterns.
• Support the regression testing, production hardening, and monitoring of deployed tools.

C. Process & Controls

• Ensure consistency in KPIs, metrics, and visualizations by aligning with centralized reporting logic.
• Document code, logic, and assumptions clearly to ensure auditability and team-wide understanding.
• Participate in code reviews, design discussions, and architectural evolution of the analytics stack.

About You:

You are a curious, detail-oriented engineer who’s excited about solving real business problems through data and software. You enjoy owning features end-to-end, thrive in collaborative environments, and seek to make measurable impact through code.

Qualifications and Experience Required:

• Bachelors' degree in Computer Science, Data Science, or other rigorous technical discipline.
• 5+ years of experience building data-driven applications, dashboards, or analytical tooling.
• Proficiency in programming (e.g., Python, Pyspark, SQL, JavaScript, TypeScript) and frontend frameworks (e.g., React).
• Familiarity with cloud platforms (e.g., Azure, GCP, Snowflake, Databricks or Palantir).
• Strong understanding of software engineering principles including version control (Git), modularity, and testing.
• Comfortable working with large datasets and integrating with data pipelines.
• Strong communication skills and ability to work effectively across technical and business stakeholders.
• A proactive mindset, team-first attitude, and a passion for solving problems that matter.