Squarepoint is a global investment management firm that utilizes a diversified portfolio of systematic and quantitative strategies across financial markets that seeks to achieve high quality, uncorrelated returns for our clients. We have deep expertise in trading, technology and operations and attribute our success to rigorous scientific research. As a technology and data-driven firm, we design and build our own cutting-edge systems, from high performance trading platforms to large scale data analysis and compute farms. With offices around the globe, we emphasize true, global collaboration by aligning our investment, technology and operations teams functionally around the world.
Role: Software Developer - Data Pipelines
Team: Alpha Data
Department: Development
Location: London, Montreal, Singapore
The Data Development group manages the lifecycle of data used for trading, back-testing, and research at Squarepoint. We work with quantitative researchers and tech teams to integrate, process, and serve data from a huge variety of sources into our data infrastructure.
We are currently seeking new data developers to join our Alpha Data team, where teamwork and collaboration are encouraged, excellence is rewarded and diversity of thought and creative solutions are valued. Our emphasis is on a culture of learning, development, and growth.
Alpha Data is a group of fast-paced Python development teams working closely with quantitative researchers to design, build, test, and maintain data applications serving investment teams across the entire Squarepoint organization.
Alpha Data teams are able to deploy valuable data to the rest of the Squarepoint business at speed. Ingestion pipelines and data transformation jobs are resilient and highly maintainable. Data models are carefully designed in close collaboration with our domain experts for efficient query construction and alpha generation. Alpha Data developers also support their pipelines in production during live trading, and contribute to our data platform by building new frameworks, libraries, and services used to increase the team's quality of life, throughput, and code quality.
Position Overview:
- Acquire a deep understanding of the data requirements of investment research teams to deliver the right solutions to them.
- Design, implement, test, optimize and troubleshoot Python data applications, frameworks, and services.
- Collaborate with technologists and investment researchers to ensure that our data applications and data platform meet evolving business requirements.
- Work closely with data operations and data platform developers to improve our data platform and reduce our technical debt; increase the team's quality of life.
- Write and review technical documents, such as requirements docs for researchers, design docs to propose new platform solutions, and production support runbooks.
- Regularly take the lead on production support operations - during normal working hours only.
Required Qualifications:
- Only candidates with more than 2 full years of relevant experience will be considered.
- Bachelor's degree in a STEM subject.
- Strong skills programming in Python in a Data Engineering context.
- Experience with and knowledge of SQL and common RDBMS systems.
- Practical knowledge of commonly used protocols and tools used to transfer data (e.g. FTP, SFTP, HTTP APIs, AWS S3).
- Excellent communication skills.
Nice to have:
- Experience with big data frameworks, databases, distributed systems, Cloud or Web development.
- Experience with any of these: C++, kdb+/q, Rust, JavaScript, TypeScript, React.