The Role
We are seeking an experienced Platform Engineer to join our Trade& Platform Support Engineering team in Singapore. You will be part of a global group that delivers front-line support for our proprietary quantitative-trading platform. Working alongside colleagues in the UK and the US, the team provides follow-the-sun coverage—24/7 monitoring and support of Schonfeld’s trading environment—while partnering closely with Development, Infrastructure, and Networking teams to ensure the platform’s connectivity, hardware, and software remain reliable, maintainable, and high-performing.
What you’ll do
Serve as the first point of contact for production issues, support requests, and alerts.
Investigate and resolve incidents or outages in real time, escalating when necessary.
Collaborate with Infrastructure and Networking teams to monitor connectivity and hardware across the investment platform.
Work directly with Portfolio Managers on project work and ad-hoc support requests.
Manage regional Change Control and lead Incident Management processes.
Partner with software-development teams to ensure smooth deployment of new code to production.
Automate recurring processes and workflows, and build internal tooling to improve efficiency and system resilience.
What you’ll bring
What you need:
Minimum 5 years of experience in financial services supporting trading and post-trade systems
Experience in managing large scale deployments/environments
Experience supporting applications in a Linux environment
Strong scripting skills – Python, Bash, Shell, Perl
Experience developing tools and/or automating processes
Experience with supporting FIX protocol
An understanding of monitoring, and performance management
Excellent verbal and written communication skills
Strong ownership experience and at rack record of delivering results
A degree in Computer Science, Engineering, or a related field
We’d love if you had:
Experience performing FIX certification/onboarding
Experience with NFS and GPFS filesystems
Knowledge of storage devices
Experience with application monitoring systems such as ITRS Geneos
Experience with Control-M job scheduling
Knowledge of q and kdb+
Experience with AWS
Experience with Docker