Software Engineer

• 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 to maintain and 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).

The Engineering team at Modular is core to the firm, powering data, operations, and risk functions. We build and maintain the technology that keeps the firm's workflows running smoothly, efficiently, and safely. This isn't a narrow role: our engineers work across software development, data engineering, infrastructure, and automation. We're a small team that moves quickly, similar to a startup.

We're looking for an engineer who likes working across the whole 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 is mainly Python and Golang, running on Kubernetes.

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.

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.

• Build and maintain data pipelines that support reporting, risk monitoring, and analytics.
• Build tools to pull in, clean up, check, and analyze data, both structured and unstructured.

• Build and support connections to exchanges and other outside systems (FIX, APIs).
• Make sure these connections are secure, reliable, and properly monitored.

• Help with CI/CD, containers, logging, and alerting.
• Support and improve cloud deployments (AWS, GCP, or Azure) running on Kubernetes.