As an Engineering Manager on the Market Data & Analytics team within the Institutional product group, you’ll lead a team of engineers building and scaling the real-time market data and analytics platform that powers trading systems. This team owns index and reference price calculation, market data ingestion and distribution, and funding rate computation – the data systems that trading, risk, and clearing depend on. You’ll drive technical strategy, grow a high-performing team, and deliver accurate, low-latency data that institutional clients and downstream exchange services rely on.

What you’ll do:

• Own the technical roadmap for market data and analytics domain, aligning priorities with Institutional product goals and driving execution from planning through delivery.
• Lead and grow a team of 5-10 engineers through hands-on coaching, career development, and a high bar for technical excellence.
• Partner with Product, Design, and cross-functional engineering teams (Exchange, Derivatives, Prime, Risk) to scope, sequence, and ship features that expand market data and analytics capabilities.
• Drive data accuracy, reliability, and performance, ensuring index pricing and market data feeds meet strict correctness, latency, and uptime requirements at scale.
• Shape engineering culture and hiring for your team, building a pipeline of exceptional talent and maintaining high standards for code quality and operational rigor.

Required Skills and Experience:

• 8+ years of software engineering experience, including 3+ years managing engineering teams building high-throughput, low-latency distributed systems.
• Proven track record delivering real-time data, market data, or financial infrastructure systems processing high volumes with strict accuracy and reliability requirements.
• Deep technical fluency in systems design, streaming/data pipelines, and at least one backend language (e.g., Java, Kotlin, Go, C++) sufficient to guide architecture decisions and unblock your team.
• Demonstrated success hiring, developing, and retaining senior engineers, with measurable outcomes in team growth and retention.
• Experience partnering with Product and business stakeholders to translate complex requirements into clear engineering plans with well-defined milestones.
• Utilizes generative AI responsibly, maintaining human oversight to deliver business-ready outputs and drive measurable improvements in workflow efficiency, cost, and quality.

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