Senior Engineer, Systematic Research Technology

Balyasny Asset Management L.P.; Greater London; On-site; GBP 70,000 - 90,000; Full time

Job summary

Balyasny Asset Management L.P. is looking for a skilled Senior Engineer for their Systematic Data team in Greater London. The role focuses on designing and maintaining cloud-native data systems critical for systematic trading operations. Candidates should have a degree in Computer Science and over 5 years of experience in software development. Knowledge of Python, system architecture, and financial markets is essential. This exciting position offers the chance to contribute to data quality and integration within a dynamic team.

Qualifications

• 5+ years of hands-on development experience in production systems.
• Strong understanding of full technology stack.
• Experience in a front office trading environment preferred.

Responsibilities

• Design and maintain cloud-native, high-performance data systems.
• Collaborate with alpha research teams for data integration.
• Enhance operational scale and stability of the platform.

Skills

Python

System architecture

Collaborative software development

Clean code principles

Time-series data

Linux scripting

Financial markets knowledge

Education

Degree in Computer Science or related field

Tools

Postgres/MSSQL

AWS

Docker

Job description

The Systematic Data team is seeking a highly skilled and experienced Senior Engineer to support the rapidly growing systematic trading business. Data is the lifeblood of systematic trading and the capabilities we deliver are critical to the success and scalability of the business.

As a key member of our dynamic team, you will be responsible for the design, implementation, and maintenance of cloud-native (AWS), high-performance data acquisition, storage, and retrieval systems/APIs (including real-time data). The platform must also ensure the quality and availability of our data historically and ongoing.

You are an excellent communicator, able to work directly with our systematic alpha research teams to on-board and profile new datasets into the platform and support research projects. A self-starter, you can manage time effectively across multiple projects and with competing priorities. You are highly collaborative and will build strong working relationships within our team and with our stakeholders. You are naturally curious, analytical in your approach to problems and able to deal positively with conflicting views. You are constantly looking for opportunities to further accelerate alpha discovery, reduce time to market and improve operational scale/stability through enhancements to our platform and processes, and through ensuring optimal alignment and integration with the systematic research process.

Requirements

• Degree in Computer Science or a related field with computational focus
• 5+ years of hands-on development experience building and supporting production systems
• Highly skilled in Python, comfortable with different programming styles (e.g. OO, functional) and strong on design patterns
• Strong understanding of system architecture and the full technology stack (software, OS, CPU/memory, local/network storage, networking, etc.)
• Proponent of collaborative software development approaches: version control, CI/CD, automated testing, code review, refactoring, and related approaches
• Craftsman-like approach to building software, taking pride in clean and efficient code, and instilling these values in others
• Strong knowledge of one or more relevant database technologies (e.g. Postgres/MSSQL, Redshift/Snowflake, KDB/OneTick)
• Solid understanding of time-series data and temporal queries
• Linux platforms and related scripting
• Understanding of financial markets and instruments (particularly cash equities)
• Experience in a front office trading environment (e.g. hedge fund or investment bank) – ideally systematic/quantitative in nature

Beneficial

• Proficient in one or more OO programming languages (e.g. Java/C#)
• Experience with datasets used for cash equity research and trading
• Experience with distributed computing (e.g. Spark/Dask, Slurm/HTCondor)
• Experience with event-driven, asynchronous architectures and related messaging technologies (e.g. Kafka, MQ)
• Experience with cloud platforms (e.g. AWS, GCP, Azure)
• Experience with orchestration and container technologies (e.g. Airflow, Kubernetes, Docker)
• Experience with monitoring and alerting tools (e.g. CloudWatch, Prometheus, Grafana, Sentry/OTel)