Data Systems Team Lead

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.

• →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.
• →Ensure reliability, uptime, and effective capacity planning for data workloads.
• →Partner with stakeholders across research, trading, and engineering to align data workflows with business needs.
• →Standardize ingestion, schema management, lineage, permissions, and audit processes.
• →Investigate upstream data sources, identify root causes of data issues, and implement sustainable corrective actions.

• 10+ years of experience as a Data Systems Engineer delivering production data platforms, with 2+ years leading and mentoring engineering teams.
• Proven ability to design, scale, and optimize data pipelines and distributed systems in production.
• Deep data platform fundamentals, including batch and streaming processing, scalable table/metadata formats, object storage, and SQL.
• Hands-on experience building scalable ingestion and orchestration workflows, g., reliable scheduling, dependency management, backfills, and recovery.
• Experience with modern data architecture patterns and making tradeoffs across performance, reliability, and cost
• Solid understanding of data storage and file/table lifecycle management
• Ability to make architectural decisions across IT solutions, system design, and implementation—ensuring maintainability and extensibility.
• Demonstrated track record of improving reliability and operational excellence for data systems
• Excellent stakeholder communication skills, with strong roadmap ownership and the ability to align engineering delivery with business needs.
• Ability to drive large-scale change while iterating safely—planning rollouts, learning from outcomes, and adjusting direction when required.
• Strong problem-solving mindset with high attention to detail, including root-cause analysis of data/system issues.
• Prior experience in quant trading or financial services is highly desirable.
• University degree in Computer Science or a related discipline.
• Fluency in written and spoken English.