We are partnered with a Tier-One, Multibillion Dollar Quantitative Hedge Fund who are hiring a Data Engineer into its quantitative research and trading platform.
This is a high-impact opportunity for candidates with experience in data engineering, market data, or research infrastructure within demanding technical environments. The firm is investing heavily in its data platform and is seeking an outstanding engineer to help build and scale the infrastructure that underpins systematic research, trading, and portfolio decision-making.
You will join a deeply technical environment with serious investment in data architecture, compute, and research infrastructure, working on systems that support a sophisticated quantitative platform across the full lifecycle of data ingestion, storage, quality, accessibility, and delivery.
The opportunity - This role sits at the core of a high-performance investment platform and focuses on building robust, scalable data systems that power researchers, PMs, and trading teams.
The scope includes:
- Research data infrastructure
- ETL / ingestion pipelines
- Data quality and validation frameworks
- Historical time-series management
- Real-time and batch data delivery
- Integration of external vendor and broker data
- Scalable storage and compute architecture
This is an opportunity to work on large-scale, high-value datasets in an environment where data is central to research quality, trading performance, and platform edge.
Candidate profile
- 5-15 years’ experience in data engineering, market data engineering, or data platform development
- Experience gained in a quant hedge fund, systematic trading firm, proprietary trading environment, electronic market maker, sell-side electronic trading / prime services business, major data vendor, or other highly demanding data-intensive environment
- Strong experience building and maintaining scalable data pipelines and data platforms
- Expertise in handling large structured and unstructured datasets
- Strong understanding of market data, historical time-series data, and data architecture in performance-sensitive environments
- Experience with tick, intraday, end-of-day, reference, fundamental, alternative, or execution-related datasets
- Strong knowledge of data quality, validation, lineage, and governance
- Experience integrating external vendor feeds, broker data, and third-party data sources
- Strong engineering capability across batch and real-time / streaming systems
- Excellent programming and systems design skills
- A high level of comfort working in technically rigorous, low-tolerance-for-error environments
Why this role - This is an opportunity to join a firm with:
- A world-class quantitative platform
- Substantial data and compute resources
- Technically demanding, high-value engineering problems
- Direct exposure to a leading systematic investment business
- Meaningful ownership over critical platform infrastructure
- A high-performance culture where strong engineering work has immediate and visible impact
- For the right person, this is a chance to build infrastructure at the centre of a top-tier quant platform, where data quality, scale, and speed directly influence research output and trading performance.