Data Engineer Intern: Build AI-Driven Healthcare Data Pipelines (Singapore)

re-zoo-me; Singapore; On-site; SGD 20,000 - 27,000; Full time

Job summary

Fullerton Health Group is seeking a Data Engineer Intern to join our Data & AI team in Singapore. You will build data pipelines and data platforms powering AI-driven healthcare automation across the region, owning real deliverables on live systems with mentorship from senior engineers.

You will gain hands-on experience with production datasets, EDWH pipelines, and modern cloud data architectures on Azure, while learning governance and cross-border data handling in a regulated industry.

Qualifications

• Pursuing a Bachelor’s or Master’s degree in a related field.
• Proficiency in Python and SQL.
• Understanding relational databases and data modeling.
• Familiarity with Git and software engineering practices.
• Strong analytical thinking and attention to detail.
• Good written and verbal English communication.

Responsibilities

• Build and maintain ETL/ELT pipelines under senior engineers.
• Integrate data from multiple sources (Claims, Member Data, Finance, APIs).
• Write and optimize SQL queries and assist with data modeling.
• Work with Azure Data Services (Blob Storage, Data Lake, Azure SQL, Data Factory).
• Implement data quality checks, validation rules, and logging.
• Prepare and clean structured and semi-structured datasets for AI models.
• Assist in building dashboards and reports for operations monitoring.
• Document pipelines, data flows, and technical decisions.

Skills

Python

SQL

Data modeling

Analytical thinking

English communication

Git

Education

Bachelor’s or Master’s degree in CS/DS/IS/Engineering

Tools

Azure Data Services

Job description

Fullerton Health Group is seeking a Data Engineer Intern to join our Data & AI team in Singapore. You will build data pipelines and data platforms powering AI-driven healthcare automation across the region, owning real deliverables on live systems with mentorship from senior engineers.

You will gain hands-on experience with production datasets, EDWH pipelines, and modern cloud data architectures on Azure, while learning governance and cross-border data handling in a regulated industry.