Senior Market Data Platform Engineer (Python) | Dynamic Asset Management Leader
5 days ago
City of London
[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 ...