Platform Engineer

A leading firm in quantitative investment, dedicated to leveraging advanced technology and data analysis to drive investment strategies. Our mission is to innovate and excel in the financial markets through collaboration and cutting‑edge solutions. About the Role The role involves working closely with the Quantitative Development team to enhance our technology platform and support the quantitative investment business through software contributions and operational excellence.

Responsibilities Quantitative Development: Work directly as a member of the Quantitative Development team, collaborating daily with other Quantitative Developers, Researchers, and Portfolio Managers. Platform Development: Provide software contributions to evolve the infrastructure platform, building foundational technology for the entire quantitative investment business. Contributions will include: Build cutting‑edge CI/CD pipelines for continuous delivery, leveraging the latest technology in automated build systems, integration testing, and environment management.

Leverage Kubernetes, OpenShift, and the latest open‑source technologies to automate distributed deployments across multiple nodes. Automate the management of key infrastructure using tools such as Terraform and the AWS CDK. Manage compute capacity across the entire Quant fleet, ensuring our ability to scale to support growing business needs.

Deploy and manage key distributed systems, optimize performance, and ensure continuous uptime. Work with databases (relational, non‑relational) and key data storage layers, including network filesystems and cloud‑based storage. Enable critical alpha research and strategy development workflows by partnering directly with the Quantitative Research team to ensure environment, dependency, and compute needs are met.

Tech Strategy: Participate in shaping the future of our technology platform, making foundational decisions on technology that will dictate our success, including: Workflow management and orchestration: Define strategies to help meet the complex needs of online and offline quantitative workflows. Compute strategy: Help facilitate our adoption and migration of cloud computing, in partnership with on‑prem compute in a cloud‑hybrid setup. Data strategy: Define a data platform that will allow us to sidestep scaling bottlenecks while remaining productive and help manage our ever‑growing and diverse quant datasets.

Access Control: Define systems for authorization, permissions, and policy enforcement to help boost group productivity while protecting critical investment IP. Dependency management: Support a constantly evolving, cross‑language dependency chains, involving both first and third‑party dependencies. Development process: Define robust standards and processes to help the team avoid outages and ship higher quality code.

Operational Excellence: Define strategies, systems, and toolkits to maintain continuous uptime to support trading systems, applications, and research. Participate in supporting trading strategies and platform infrastructure. Research Tools: Build and maintain sophisticated tools and software to facilitate data analysis, modeling, portfolio simulation, and trade execution.

Qualifications Bachelor’s or advanced degree in Computer Science, Mathematics, Statistics, Engineering, or related field. Required Skills Strong ability to prioritize and multi‑task. Demonstrated ability to think independently, identify creative approaches to complex problems, and articulate those ideas clearly through verbal, written, and visual media.

Programming proficiency, preferably in Java, Python, and R. Experience in UNIX/Linux/BSD environments is required. Strong grasp of high‑level design and system architecture in software systems.

Background using database technologies, including relational and no‑SQL databases. Experience with one or more market‑leading cloud platforms, including AWS, GCP, or Azure. Experience with containerization and dependency management (Docker or Podman a plus).

Experience with Kubernetes (OpenShift a plus), or similar cloud‑based deployment managers such as Amazon ECS. Background writing unit and integration tests using the latest testing platforms in Python and Java (pytest, JUnit, Mockito). Experience with distributed filesystems as a plus.

Preferred Skills Experience with advanced data analysis techniques. Familiarity with financial markets and investment strategies. #J-18808-Ljbffr