A leading multi-strategy investment firm is hiring a Senior Engineer to join a front‑office engineering team responsible for the core systematic data platforms used by quantitative research and trading.
This role supports the systematic investment process end‑to‑end, sitting above basic reference data (e.g. SecMaster, prices) and closer to fundamental, derived, and alternative datasets that directly feed alpha research. The focus is on building robust, performant, and reproducible data systems rather than analytics or reporting.
This is a software‑first data engineering role. You'll be building production‑grade systems that acquisition, model, store, and expose data to systematic researchers, with a strong emphasis on correctness, performance, and operational stability in a trading environment.
Responsibilities
- Build and maintain core systematic data systems used directly by quantitative researchers
- Own ingestion, modelling, storage, and access layers for fundamental, derived, and alternative datasets
- Design data models with a strong focus on point‑in‑time correctness, versioning, and reproducibility
- Develop and operate data services, APIs, and research‑facing interfaces
- Ensure data quality, availability, and historical integrity across research and production workflows
- Support both historical and real‑time / near‑real‑time data where required
- Work closely with systematic researchers to onboard new datasets and support research use cases
- Contribute to performance, scalability, and long‑term evolution of a production‑critical data platform
Required skills & experience
- Strong experience as a Senior Engineer working on production, data‑heavy systems
- Excellent Python skills, comfortable working across object‑oriented and functional styles, with a solid grasp of design patterns
- Strong software engineering fundamentals (clean code, system design, testing, CI/CD, version control)
- Proficiency in SQL and experience working with time‑series or analytical data
- Experience designing and operating production data platforms and services (not just ETL pipelines)
- Proficiency in at least one object‑oriented language beyond Python (e.g. Java or C#)
- Comfortable working in Linux and cloud‑based environments (AWS preferred)
- Prior exposure to systematic, quantitative, or front‑office engineering environments is highly desirable
Who this suits
- Engineers who think of data platforms as core software systems
- People comfortable operating close to systematic alpha research without being researchers themselves
- Candidates who care about correctness, performance, and reproducibility over dashboards or experimentation
If you feel this role is a good match, apply today!
#J-18808-Ljbffr”, “datePosted”: “2026-05-18”, “hiringOrganization”: { “@type”: “Organization”, “name”: “Selby Jennings”, “sameAs”: “https://uk.whatjobs.com/pub_api__cpl__435628046__4861?utm_campaign=publisher&utm_medium=api&utm_source=4861&geoID=33” }, “jobLocation”: { “@type”: “Place”, “address”: { “@type”: “PostalAddress”, “addressLocality”: “London” } } }A leading multi-strategy investment firm is hiring a Senior Engineer to join a front‑office engineering team responsible for the core systematic data platforms used by quantitative research and trading.
This role supports the systematic investment process end‑to‑end, sitting above basic reference data (e.g. SecMaster, prices) and closer to fundamental, derived, and alternative datasets that directly feed alpha research. The focus is on building robust, performant, and reproducible data systems rather than analytics or reporting.
This is a software‑first data engineering role. You’ll be building production‑grade systems that acquisition, model, store, and expose data to systematic researchers, with a strong emphasis on correctness, performance, and operational stability in a trading environment.
Responsibilities
- Build and maintain core systematic data systems used directly by quantitative researchers
- Own ingestion, modelling, storage, and access layers for fundamental, derived, and alternative datasets
- Design data models with a strong focus on point‑in‑time correctness, versioning, and reproducibility
- Develop and operate data services, APIs, and research‑facing interfaces
- Ensure data quality, availability, and historical integrity across research and production workflows
- Support both historical and real‑time / near‑real‑time data where required
- Work closely with systematic researchers to onboard new datasets and support research use cases
- Contribute to performance, scalability, and long‑term evolution of a production‑critical data platform
Required skills & experience
- Strong experience as a Senior Engineer working on production, data‑heavy systems
- Excellent Python skills, comfortable working across object‑oriented and functional styles, with a solid grasp of design patterns
- Strong software engineering fundamentals (clean code, system design, testing, CI/CD, version control)
- Proficiency in SQL and experience working with time‑series or analytical data
- Experience designing and operating production data platforms and services (not just ETL pipelines)
- Proficiency in at least one object‑oriented language beyond Python (e.g. Java or C#)
- Comfortable working in Linux and cloud‑based environments (AWS preferred)
- Prior exposure to systematic, quantitative, or front‑office engineering environments is highly desirable
Who this suits
- Engineers who think of data platforms as core software systems
- People comfortable operating close to systematic alpha research without being researchers themselves
- Candidates who care about correctness, performance, and reproducibility over dashboards or experimentation
If you feel this role is a good match, apply today!
#J-18808-Ljbffr…