Develop high-quality Python applications for front-office trading systems
Partner with traders and quantitative researchers to improve trading and execution workflows
Translate business and quantitative requirements into scalable system designs and implementation plans
Design, build, and troubleshoot complex technical solutions beyond conventional approaches
Write secure, production-grade code and conduct code reviews
Identify and automate solutions for recurring system issues to improve stability
Drive adoption of modern technologies and best practices across engineering teams
Align with both technical and non-technical stakeholders to ensure successful delivery
You will be part of a high-performing team within a global financial services organization, working at the intersection of technology and markets.
The team focuses on delivering innovative solutions that support trading, risk management, and liquidity provision across global markets.
This role offers the opportunity to push technical boundaries while working on cutting-edge systems within equities technology.
As a Lead Software Engineer, you will play a key role in designing, building, and delivering scalable, secure, and high-performance solutions that support front-office trading activities.
You will collaborate closely with traders and quantitative researchers to enhance trading workflows and execution capabilities.
Requirements
Bachelor’s degree in Computer Science or a related field
At least 5 years of experience in software engineering
Strong expertise in capital markets and equity market microstructure
Deep understanding of electronic trading workflows (pre-trade analytics, signal generation, execution, post-trade analysis)
Advanced proficiency in Python
Strong analytical, quantitative, and problem-solving skills
Ability to design scalable architectures from business and quantitative requirements
Experience in quantitative trading or market analysis
Familiarity with KDB/q
Knowledge of FIX protocols, market data systems, and order management systems
Exposure to internal quant platforms (e.g., SecDB, Athena, Quartz) is a plus
Experience with data streaming technologies such as Kafka or AMPS
Application:
Apply to this job posting, and email your CV with the job title as the subject line to: *************