Data Engineer

About the team

The Medex Insights & Monitoring team enables data‑driven decision‑making for the global Medex portfolio. The team ensures timely, accurate, and meaningful insights on experience, performance, and portfolio behaviour, supporting stakeholders in Technical Accounting, Experience Studies, Pricing, and Portfolio Steering.
The team monitors client and portfolio metrics, automates recurring insight pipelines, and enhances transparency through scalable dashboards and analytics.

About the role:

In this role, you will develop, enhance, and maintain data pipelines and monitoring datasets that underpin Medex performance reporting. You will support analytical investigations, improve data quality processes, and help automate recurring monitoring activities.
Responsibilities include ensuring data accessibility and reliability, optimizing the company's data ecosystem, and setting up scalable data platforms. Additionally, the role focuses on delivering complex data-driven projects, enhancing business intelligence capabilities, and creating impactful data visualizations. The role requires strong technical execution, attention to detail, and the ability to collaborate closely with data engineers, actuaries, and analysts across the business.

Key responsibilities:

• Build and maintain stable and efficient data pipelines used in Medex monitoring.
  
  
• Design and optimize SQL, Python, or R scripts to automate data preparation steps.
  
  
• Perform root‑cause analysis of data issues and coordinate remediation with relevant teams.
  
  
• Lead monitoring refresh cycles and ensure timely availability of updated datasets.
  
  
• Improve validation logic, introduce new quality checks, and refine monitoring indicators.
  
  
• Support deeper analytical reviews on claims, exposures, trends, and portfolio performance.
  
  
• Automate repetitive processes in monitoring workflows, including dataflows, script‑based updates, and scheduled refreshes.
  
  
• Enhance dashboards, KPI definitions, and underlying data structures for consistency and accuracy.
  
  
• Develop reusable components and templates for monitoring processes.
  
  
• Work closely with Data Engineering, Experience Studies, Pricing, and Technical Accounting teams to align data definitions and structures.
  
  
• Support UAT for new dashboards, pipeline enhancements, or monitoring logic changes.
  
  
• Communicate insights, issues, and recommendations clearly and proactively.

About You

• Bachelor’s degree in Statistics, Mathematics, Data Science, Engineering, Economics, Actuarial Science, or related field.
  
  
• 3–5 years of relevant experience in data engineering and analytics, preferably in the field of Insurance.
  
  
• Strong SQL and Pyspark skills and hands‑on experience working with relational databases.
  
  
• Working proficiency in Python or R for data processing and automation.
  
  
• Experience with Power BI or similar visualization tools.
  
  
• Good understanding of data pipelines, validation logic, and monitoring frameworks.
  
  
• Strong analytical and problem‑solving capabilities, familiarity with GLMs and Machine Learning Models.
  
  
• Ability to manage recurring responsibilities reliably while improving underlying processes.
  
  
• Clear communication skills and the ability to collaborate with multiple technical and non‑technical teams.
  
  
• Proactive mindset with a focus on enhancing data quality and operational efficiency.