Cloud Data Engineer for AI-Driven Fintech

Engg; Singapore; On-site; SGD 90,000 - 150,000; Full time

Job summary

Visa is seeking a Data Engineer in Singapore to design, build, and optimize data platforms powering secure fintech solutions. You will code hands-on with data and modern tools—AI-assisted development, cloud services, and automation—while aligning with product, security, and regulatory requirements.

Collaborate with product managers, designers, data scientists, QA, operations, and compliance to translate business needs into robust data pipelines, maintain data quality, and support real-time

Qualifications

• Bachelor's degree or 3+ years of relevant work experience in data engineering.
• Experience gathering requirements from stakeholders for data projects.
• Experience interpreting requirements and executing designs under guidance.
• Experience coding across components with security in mind.
• Experience in code reviews and feedback.

Responsibilities

• Attend meetings with stakeholders to learn requirements and data needs.
• Design and implement data components following standards and security.
• Develop code across components with best practices and security checks.
• Participate in code reviews to improve quality.
• Conduct unit testing and support testing in shared environments.
• Develop tools and automation for batch and real-time data processes.
• Collaborate to create data extraction queries and simple orchestration.
• Monitor data pipelines, escalate alerts, and implement basic fixes.

Skills

Data engineering

Stakeholder meetings

Code development

Unit testing

Data transformation

Education

Bachelor's degree

Tools

Cloud services

Automation frameworks

AI-assisted development

SQL/ETL

Job description

Visa is seeking a Data Engineer in Singapore to design, build, and optimize data platforms powering secure fintech solutions. You will code hands-on with data and modern tools—AI-assisted development, cloud services, and automation—while aligning with product, security, and regulatory requirements.

Collaborate with product managers, designers, data scientists, QA, operations, and compliance to translate business needs into robust data pipelines, maintain data quality, and support real-time