Software Developer – Data Services (KDB+/Q)

Team: Data Services

The Data Development group manages the lifecycle of data used by investment for trading, backtesting and research. We work with quants and tech teams to integrate, process and serve data from vendors and public sources in Squarepoint's data infrastructure (alpha data and cross-asset referential data).

We are currently seeking new data developers to join our growing teams. You will be part of a learning culture, where teamwork and collaboration are encouraged, excellence is rewarded and diversity of thought and creative solutions are valued.

Reference Data Services teams work closely with portfolio managers to design, implement, test and maintain Squarepoint's service-oriented database architecture for research and production. They work primarily in kdb+ and own Squarepoint's core model of reality, normalize many datasets to that model, and expose that model through robust, redundant, scalable infrastructure with an uptime greater than 99.999% during trading hours. There is a strong operational component to the role, as they act as level 2+ support for these services during live trading.

Position Overview:

• Acquire a deep understanding of the data requirements of investment research teams to deliver the right solutions.
• Design, implement, test, optimize and troubleshoot kdb+/q data pipelines, frameworks and services.
• Work closely with data operations and data platform developers to improve our data platform and reduce our technical debt.
• Collaborate with and influence technologists and investment researchers to ensure our reference data services meet constantly evolving requirements.
• Write and review technical documents, such as requirements docs for researchers, design docs to propose new platform solutions and production support runbooks.

Required Qualifications:

• Bachelor's degree in a STEM subject.
• 2+ years development experience with kdb+/q.
• Excellent communication skills.

Nice to have:

• 2+ years designing, testing, optimizing and troubleshooting data intensive applications.
• Experience analyzing and organizing financial data.
• Experience with any of these: SQL, JavaScript, TypeScript, React, C++, KDB+/Q, Rust.