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Data Engineer, Research Platform.
Build the clean, reliable market-data foundations that make fast experimentation and reproducible quantitative research possible.
What we do
We create the research data platform that gives quantitative teams trusted access to market information. Our systems turn large volumes of raw, time-sensitive data into reliable datasets that can be explored, reproduced and used with confidence.
What you will do
- Build and operate pipelines for tick, reference and derived market data.
- Design data models and interfaces optimised for quantitative research workflows.
- Improve data quality checks, lineage, observability and recovery processes.
- Collaborate with researchers to make large-scale analysis faster and reproducible.
- Evaluate storage and compute choices as data volume and use cases evolve.
What we are looking for
- Strong Python skills and experience building production data pipelines.
- Knowledge of SQL, columnar storage and time-series data patterns.
- Experience with distributed processing, workflow orchestration or cloud platforms.
- A methodical approach to data quality and operational ownership.
- Ability to translate research needs into simple, dependable platform capabilities.
Prepare with clarity
Interview guide for this role
You’ll complete two technical evaluations. Depending on the role and stage, we may prefer to conduct a technical evaluation in person.
- Expect a data-modelling and SQL exercise using time-series or market data.
- Prepare to design an observable pipeline with clear quality checks, lineage, recovery and scaling choices.
- Be ready to discuss storage formats and query patterns for large analytical datasets.
- Bring an example of a data-quality or reliability incident you investigated and how you prevented recurrence.
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RoleData Engineer, Research Platform
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