Senior Software Engineer - Systematic Data
Job Description
[Up to c. £250k Comp Package | Office-Led Working]
Role Overview
We’re representing a global investment manager expanding the engineering capability behind its systematic trading business. This London hire will sit within a specialist data engineering function responsible for making high-quality financial datasets reliably available to quantitative research and investment teams.
This is fundamentally a software engineering role focused on systematic data, rather than a conventional ETL or pipeline position. You will help engineer the services and platform capabilities used to acquire, validate, store and query both historical and real-time datasets, while working directly with researchers to bring new data into production. The mandate suits an experienced Python engineer who combines strong software design with an understanding of systems, financial data and front-office research workflows. There is meaningful ownership across engineering, dataset onboarding and production reliability...
Role Snapshot
- Typically 5+ years of hands-on production software engineering experience, supported by a Computer Science or similarly computational degree
- Strong Python engineering depth, including object-oriented design, multiple programming paradigms, reusable architecture and established software design patterns
- Engineer and evolve data acquisition, storage, retrieval and API capabilities supporting both historical and real-time systematic research datasets
- Bring new datasets onto the platform end-to-end, including technical profiling, integration, validation, productionisation and ongoing availability
- Understand systems beyond application code, including Linux, networking, CPU and memory behaviour, storage architecture and the performance implications of technical design decisions
- Work confidently with relational, analytical or time-series database technologies, with strong understanding of temporal data structures and query patterns
- Bring prior front-office financial-markets experience from a hedge fund, asset manager, systematic trading business or investment bank, ideally including cash-equities data
- Apply disciplined software-engineering practices across version control, automated testing, CI/CD, code review, refactoring, maintainability and production support
- (Preferred) Additional experience with Java or C#, distributed computing, asynchronous or event-driven systems, Kafka or comparable messaging technologies
- (Preferred) Exposure to cloud infrastructure, workflow orchestration, containers and modern observability tooling across technologies such as AWS, Airflow, Kubernetes, Docker, Prometheus, Grafana or OpenTelemetry
...
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