Software Engineer

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

Overview

The Engineering team at Modular is core to the firm, powering data, operations, and risk functions. We build andmaintainthe technology that keeps the firm's workflows running smoothly, efficiently, and safely. Thisisn'ta narrow role: our engineers work across software development, data engineering, infrastructure, and automation.We'rea small team that moves quickly,similar toa startup.

Job Description

We'relooking for an engineer who likes working across thewhole system, not just one part of it. That means you might build a data pipeline, then help run it reliably, then work on the infrastructure it sits on, then help connect it to an outside system. You should be comfortable owning a problem from start to finish rather than passing it off once it leaves your usual area. Depth in one or two areas is a plus, but what we need most is someone willing to work across all of them. Our stack ismainly Pythonand Golang, running on Kubernetes.

Software Engineer – Job Description

We are seeking a Software Engineer who thrives in a startup‑like environment and enjoys contributing across multiple engineering disciplines—including software development, data engineering, infrastructure, and automation. In this role, you will design, build, and maintain mission‑critical systems that enhance efficiency, reduce operational risk, and improve the reliability of core processes. While you may bring depth in specific areas, you will have the opportunity to work across the full engineering stack and help shape the firm’s technology foundation.

Key Responsibilities

Operational Automation

• Build and improve automation tools and workflows to cut down on manual work.

• Update old scripts by moving them into workflow tools like Airflow.

Data & Analytics Engineering

• Build andmaintaindata pipelines that support reporting, risk monitoring, and analytics.

• Build tools to pull in, clean up, check, andanalyzedata, both structured and unstructured.

Systems & Connectivity

• Build and support connections to exchanges and other outside systems (FIX, APIs).

• Make sure these connections are secure, reliable, and properlymonitored.

Infrastructure & Reliability

• Help with CI/CD, containers, logging, and alerting.

• Support and improve cloud deployments (AWS, GCP, or Azure) running on Kubernetes.

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, which is what we use here.

• Some familiarity with Kubernetes.

• A problem solver who builds things that are easy tomaintainand sees them through to production.

• A clear communicator who works well in a small team that moves quickly.

Bonus skills

• Experience with FIX or other financial system integrations.

• Practical experience with cloud infrastructure (AWS, GCP, or Azure).

• Experience with data engineering or ML/AI pipelines.

• Deeper Kubernetes experience (scaling, deployments, troubleshooting).