Senior Java Developer Data Engineering

at  JJA James Joseph Associates

Posted by
Tom Owens
Recruiter
Our client is a leading and well-established player in the Quantitative Systematic trading space. The business is very well capitalised and has recently expanded its front office team of Quants and Traders. As a consequence, the need has arisen to increase the headcount on their data engineering and analytics team as the need has arisen to build a new real-time streaming data platform and enhance the capability of their data lake.
Our client is looking for the very best and you will be working with an exceptionally talented team with a flat management structure. This will be a business facing role where you are given the freedom to build solutions in the way you see fit to ensure that your front office clients have the tools, they need to enhance profitability. In return they are offering above-market basic salary in addition to exceptional bonuses…
THE ROLE: Senior Java Developer Data Engineering

The Data Engineering and Analytics team own all of the Data that is required for offline regression analysis, by far their largest client base is the front office Quants and Traders. The core of the firm’s architecture is coded Java (With Rust and C++ utilised for particularly latency sensitive activities) and this team will be utilising Kafka to stream data. Any experience with APIs e.g. REST and WebSocket experience will also be useful, and they have recently introduced ClickHouse (Although prior experience is not required) Whilst lower-level data engineering skills are essential it is important to note that this is a business facing role so the successful applicant will enjoy interaction with end users and delivering solutions fit for purpose. A smaller part of the role will also involve utilising BI tools to present data in an effective manner for business users.

• Collaborate with Quantitative Research and Trading teams to identify their data needs.
• Develop high-speed, near real-time event-driven datasets using live trading and market data.
• Create solutions for efficient and reliable extraction of insights from all collected market data.
• Integrate with external APIs to gather necessary data such as market data, balances, and trades.
• Work with other development teams to adopt best practices for using the data platform.
• Maintain databases that are essential for downstream data functions.
• Play a critical part in product design, implementation, and quality assurance processes.
• Identify and implement improvements for data collection, consumption, and storage processes.
• Partner with business development, finance, and legal and compliance teams to create analytical datasets.
• Build dashboards with Business Intelligence tools to present data to business teams.

SKILLS / EXPEIRENCE REQUIRED: SENIOR JAVA DEVELOPER DATA ENGINEERING

• Several years of experience in a data engineering role with interaction in front-office environments, either on the buy-side or sell-side
• Strong programming skills in Core Java
• Proficient in developing event-driven applications using Kafka
• High proficiency in SQL and relational data modelling
• Experience working with APIs, such as REST and WebSocket’s
• Proven experience and understanding of either; high-frequency, systematic, or electronic trading systems
• Deep interest in data analytics and comprehensive knowledge of order book mechanics and book-building techniques
• Experience with databases, including tick data stores like MySQL and ClickHouse.
• Familiarity with cloud-based environments, such as AWS or GCP
  Job ID tw357

• Collaborate with Quantitative Research and Trading teams to identify their data needs.
• Develop high-speed, near real-time event-driven datasets using live trading and market data.
• Create solutions for efficient and reliable extraction of insights from all collected market data.
• Integrate with external APIs to gather necessary data such as market data, balances, and trades.
• Work with other development teams to adopt best practices for using the data platform.
• Maintain databases that are essential for downstream data functions.
• Play a critical part in product design, implementation, and quality assurance processes.
• Identify and implement improvements for data collection, consumption, and storage processes.
• Partner with business development, finance, and legal and compliance teams to create analytical datasets.
• Build dashboards with Business Intelligence tools to present data to business teams