We are a fast-growing FinTech firm leveraging cutting-edge technology in the derivatives market. We work with some of the world’s largest hedge funds and asset managers, providing analytics and execution for relative value, volatility, and macro strategies.
About the Role:
As a Lead Software Engineer, you will drive the engineering and evolution of our trade analytics platform — the backbone of our pricing, screening, and execution workflows. You will set technical direction, lead the design of robust production-grade systems, and take ownership of platform reliability, data integrity, and performance at scale. Beyond hands-on building, you will shape how engineering work is scoped and allocated across the team, mentor other engineers, and act as a force multiplier for delivery. Domain familiarity with financial markets is useful but not critical — strong platform and leadership instincts are what will define your impact here.
Responsibilities:
- Lead the architecture and development of our core analytics platform, including data pipelines, services and the API layers consumed by research applications.
- Own the end-to-end data lifecycle — ingestion, validation, storage, transformation, and retirement — ensuring reliability, latency, lineage, and coverage across financial and macroeconomic datasets.
- Plan and allocate engineering work across the team: breaking down initiatives into deliverable workstreams, balancing priorities, and ensuring the right people are matched to the right problems.
- Establish and uphold engineering standards for how models, analytics, and tooling are developed, tested, deployed, and maintained.
- Own the software lifecycle of platform components: design, code review, testing, monitoring, and continuous improvement.
- Mentor and develop other engineers through code review, pairing, and technical guidance, raising the bar for quality across the team.
- Build trade discovery and screening tools that are performant, maintainable, and extensible.
- Continuously improve platform observability, deployment practices, and developer experience.
Requirements:
- Bachelor's or Master's in Computer Science, Software Engineering, or a related technical discipline.
- Strong software engineering fundamentals: system design, clean architecture, testing, and code quality.
- 5+ years of production software experience, including demonstrated technical leadership of projects or teams.
- Expert-level Python; familiarity with C++ or Rust is a plus for performance-critical components.
- Deep, hands-on experience designing and operating data infrastructure across the full lifecycle — time-series databases, data pipelines, and API services.
- Strong instincts around performance, reliability, and operational concerns in fast-moving production environments.
- A clear communicator and effective collaborator across trading, research, and engineering functions.
If you care deeply about platform craft and want to apply it in a high-pace quant environment, we'd love to hear from you.
Originally posted on