Performance Engineer: Data-Driven Trading Systems

Supergrads; Amsterdam; Presencial; EUR 90.000 - 150.000; Jornada completa

Descripción de la vacante

Supergrads is seeking a technically curious Performance Engineer to join a team focused on understanding and improving the performance of highly complex electronic trading environments.

Advanced professional experience with Python and Networks or Linux is an absolute must-have for this role. The role sits at the intersection of systems engineering, quantitative analysis, networking and experimental research, where you’ll investigate latency sources and develop practical improvements.

Formación

• Strong knowledge of computer architecture, networking and/or Linux.
• Experience applying reverse engineering or black-box analysis to complex systems.
• Analytical mindset with data-driven experimentation.
• Experience using Python for data analysis, modelling or system investigation.
• Understanding sophisticated networking environments and stacks.
• Independent, inquisitive problem-solver with ownership.
• Collaborative with cross-disciplinary teams in engineering and trading.

Responsabilidades

• Investigating complex systems through black-box analysis and experiments.
• Data-driven research on large datasets to uncover patterns.
• Performance optimization across connectivity and trading infrastructure.
• Build and test lightweight prototypes and proofs-of-concept.
• Collaborate with traders, software engineers, hardware and infra teams.
• Analyze network behavior with large datasets and statistical methods.
• Own investigations from question to recommendation.

Conocimientos

Python

Reverse engineering

Black-box analysis

Networking

Linux

Computer architecture

Data analysis

Descripción del empleo

Supergrads is seeking a technically curious Performance Engineer to join a team focused on understanding and improving the performance of highly complex electronic trading environments.

Advanced professional experience with Python and Networks or Linux is an absolute must-have for this role. The role sits at the intersection of systems engineering, quantitative analysis, networking and experimental research, where you’ll investigate latency sources and develop practical improvements.