Eclipse Trading
proprietary trading
DataSystemsTeamLead
Neural analysis suggests this role is
optimal for Lead candidates.
“Data Systems Team Lead at Eclipse Trading”
Industry & Context.
Problem solving; Root-cause analysis
How You'll Work.
Communication Scope
Stakeholder communication
Process & Methodology
Roadmap ownership
Full Job Description
Eclipse Trading is a leading proprietary trading firm. Founded in 2007, we have over 120 employees across 4 office locations – Hong Kong (our HQ), Sydney, Shanghai and Chicago. Our trading expertise and strategies are deployed across several markets globally, focusing on various products including equity derivatives, delta one, ETFs, commodity derivatives, and cryptocurrency. Technology is inextricably linked to our trading strategies, creating an environment powered by intellectual curiosity, problem solving, and innovation. We’re looking for an experienced Team Lead to lead our newly established Data Systems Team. The team will build Eclipse’s next-generation data platform for both research and real-time trading, spanning orchestration, storage, data access, and governance at scale. By delivering reliable and consistent solutions, the team will support a wide range of stakeholders across the company, including engineers, researchers, and traders. As a Team Lead, you’ll set the vision for a centralized data framework and drive seamless orchestration, storage, and access across a wide range of datasets. This is a high-impact, long-term role focused on building new infrastructure and a new team—not applying incremental fixes to legacy systems. It also blends leadership with architecture and hands-on engineering to deliver robust, maintainable, and high-performing solutions across both hardware and software. Responsibilities and Duties Build and lead a high-performance Data Systems Team, including mentoring and career development. Define and deliver Eclipse’s data platform roadmap, balancing business and technical priorities. Design and implement a centralized data framework and the supporting applications. Develop robust, maintainable, and high-performing data pipelines. Drive performance optimizations across both hardware and software for quant research and regulatory data retention. Manage, maintain, and expand dedicated hardware infrastructure for data systems. En
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