Every day, trillions of dollars are traded on our systems. The Trade Automation and Execution (TRAX) platform enables clients to exchange value with ease, immediacy, and confidence. TRAX spans the full trade lifecycle across asset classes and provides the automation, analytics, and execution capabilities that today’s markets demand. Our mission is to simplify and optimise trading at scale. From automated order flow to predictive models and low-latency execution, TRAX is the foundation that helps financial institutions operate more efficiently, reduce risk, and uncover opportunities in fast-moving markets.

The Intraday Analytics team is the analytics backbone of TRAX. We process billions of market data points every day across multiple asset classes and transform them into analytics that guide how the world’s largest financial institutions trade.

Our real-time analytics help institutions and traders decide where, when, and how to trade, while monitoring performance as markets move. Our historical analytics provide benchmarks and insights that allow clients to evaluate and continuously improve their strategies.

Our analytics also drive the TRAX automation engine, enabling automated trading decisions and workflows. They are also exposed via external APIs, giving clients direct access to our models and insights within their own trading systems.

In short, we provide the analytics foundation that powers smarter execution, fuels automation, and helps financial institutions optimise their performance.

We’re in the early stages of re-architecting our infrastructure to support the future growth of analytics-driven trading. A key part of this transformation is expanding beyond physical machines to virtualised environments, giving us the flexibility to scale capacity as we onboard more clients and handle the ever increasing trading volumes.

As a senior engineer, you’ll have the opportunity to:

• Design and build distributed systems that balance accuracy, consistency, availability, and low latency
• Reimagine our architecture around a cloud-based Complex Event Processing (CEP) engine
• Push the boundaries of throughput using Kafka, Flink, and analytical datastores
• Lead the development of core components in our C++17 and Java 17 infrastructure stack
• Ensure the scalability and the resiliency for both real-time streaming and historical big data
• Drive engineering best practices, mentor peers, and influence technical direction across teams