Job Description
[Up to c. £250k Comp Package | Hybrid Working]
Role Overview
We’re partnering with a globally respected multi-strategy investment firm seeking a senior-level engineer to take ownership of the next generation of its market data platforms. This role calls for someone who blends deep Python engineering capability with strong object-oriented design instincts, and who understands how to ingest, structure, and optimise vast, granular financial datasets. You’ll play a central role in shaping large-scale tick-data architecture – building pipelines, improving data-lake structures, and refining storage formats to support demanding research and trading workflows…
Key Responsibilities
- Architect, build, and refine high-throughput pipelines capable of processing large volumes of real-time and historical market data
- Develop resilient, well-structured Python/OOP solutions underpinning tick-data ingestion, normalisation, storage, and replay
- Design and evolve data-lake patterns using Parquet and related columnar formats; introduce Iceberg-style table modelling where beneficial
- Implement cloud-backed processing and storage patterns – leveraging services from AWS, Azure, or GCP for scale, resilience, and cost efficiency
- Improve system performance across latency, throughput, and reliability, ensuring pipelines support fast-moving trading environments
- Work with time-series technologies such as KDB or OneTick to optimise retrieval, querying, and analytics workflows
- Collaborate closely with researchers, traders, and engineering partners to translate data requirements into robust production solutions
- Introduce validation, reconciliation, and monitoring frameworks that guarantee the accuracy and quality of market datasets
- Maintain clear technical documentation covering pipeline logic, architectural decisions, and operational procedures
What You’ll Bring…
- 7-10 years’ experience in software/data engineering, with a strong emphasis on Python and object-oriented development
- Demonstrable experience building or maintaining large-scale tick-data platforms or market-data ingestion systems
- Strong knowledge of data-lake architecture, columnar storage (Parquet essential), and modern table formats (Iceberg highly advantageous)
- Familiarity with cloud ecosystems (AWS, GCP, or Azure), including compute, storage, and workflow orchestration patterns
- Comfortable with Kubernetes, containers, and automated deployment workflows
- Strong communication skills and the ability to operate closely with quants, PMs, and trading-focused engineering teams
- A strong academic background in Computer Science, Engineering, Mathematics, or a related technical field
- (Preferred) Experience working with time-series databases such as KDB or OneTick; C++ exposure
- (Preferred) Prior exposure to financial markets – particularly equities, macro, or systematic strategies
…
Contact Detail:
Techfellow Limited Recruiting Team