Software Engineer — Data, Automation & Infrastructure

Modular Asset Management; Singapore; On-site; SGD 90,000 - 150,000; Full time

Job summary

Modular Asset Management is seeking an Engineer with broad experience across software development, data engineering, infrastructure, and automation. The role covers building data pipelines, running them reliably, and enhancing the infrastructure that supports core workflows.

Proficiency in Python and Golang on Kubernetes, with a startup-like pace, is valued. The ideal candidate thrives when solving end-to-end problems, communicates clearly, and can contribute across multiple engineering

Qualifications

• A good understanding of how systems fit together, how data, services, and infrastructure connect, and the ability to work across those parts, not just one.
• Solid basics: testing, Git, CI/CD.
• Experience with workflow tools like Airflow.
• Comfortable working with Python and Golang.
• Some familiarity with Kubernetes.
• A problem solver who builds things that are easy to maintain and sees them through to production.
• A clear communicator who works well in a small team that moves quickly.

Responsibilities

• Operational Automation: Build and improve automation tools and workflows to cut down on manual work.
• Data & Analytics Engineering: Build and maintain data pipelines that support reporting, risk monitoring, and analytics.
• Systems & Connectivity: Build and support connections to exchanges and other outside systems (FIX, APIs).
• Infrastructure & Reliability: Help with CI/CD, containers, logging, and alerting.
• Support and improve cloud deployments (AWS, GCP, or Azure) running on Kubernetes.

Skills

Systems thinking

Cross-functional

Problem solving

Testing

Git

CI/CD

Python

Golang

Kubernetes

Security awareness

Tools

Airflow

REST APIs

CI/CD pipelines

Job description

Modular Asset Management is seeking an Engineer with broad experience across software development, data engineering, infrastructure, and automation. The role covers building data pipelines, running them reliably, and enhancing the infrastructure that supports core workflows.

Proficiency in Python and Golang on Kubernetes, with a startup-like pace, is valued. The ideal candidate thrives when solving end-to-end problems, communicates clearly, and can contribute across multiple engineering