Python Data Engineer

Tempest Vane Partners
London
3 months ago
Applications closed

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The Client


This firm is a highly respected, technology-centric investment business operating across a broad range of asset classes. Their success is built on a mix of quantitative research, cutting-edge engineering and scalable data infrastructure. Engineers here play a central role: they design, build and maintain the platforms that underpin research, trading and large-scale data analysis.


It’s a collaborative environment where technical ownership is encouraged, engineering craft is valued, and impactful work directly supports sophisticated investment strategies.


What You'll Get


  • Work on the design and build of fast, scalable market-data systems used across trading and research groups.
  • Contribute to a modern engineering ecosystem: Python, cloud-native tooling, containerisation, large-scale data lake technologies.
  • Partner closely with exceptional quantitative researchers, data engineers and traders.
  • Influence architectural decisions and continuously refine pipeline performance.
  • Join a culture that values rigour, curiosity and continual improvement.
  • Benefit from strong compensation and long-term career growth within a high-performing engineering organisation.


Role Overview


  • Design, implement, and maintain high-throughput, low-latency pipelines for ingesting and processing tick-level market data at scale.
  • Operate and optimise timeseries databases (KDB, OneTick) to efficiently store, query, and manage granular datasets.
  • Architect cloud-native solutions for scalable compute, storage, and data processing, leveraging AWS, GCP, or Azure.
  • Develop and maintain Parquet-based data layers; contribute to evolving the data lake architecture and metadata management.
  • Implement dataset versioning and management using Apache Iceberg.
  • Collaborate closely with trading and quant teams to translate data requirements into robust, production-grade pipelines.
  • Implement monitoring, validation, and automated error-handling to ensure data integrity and pipeline reliability.
  • Continuously profile and optimise pipeline throughput, latency, and resource utilisation, particularly in latency-sensitive or HFT-like environments.
  • Maintain clear, precise documentation of data pipelines, architecture diagrams, and operational procedures.


What You Bring


  • 3+ years of software engineering experience, preferably focused on market-data infrastructure or quantitative trading systems.
  • Strong Python expertise with a solid grasp of performance optimisation and concurrency.
  • Proven experience designing, building, and tuning tick-data pipelines for high-volume environments.
  • Hands-on experience with Parquet storage; experience with Apache Iceberg or similar table formats is a plus.
  • Practical experience with containerisation (Docker) and orchestration platforms (Kubernetes).
  • Strong background in profiling, debugging, and optimising complex data workflows.
  • Experience with timeseries databases (KDB, OneTick) and/or performance-critical C++ components.
  • Deep understanding of financial markets, trading data, and quantitative workflows.
  • Excellent communication skills with the ability to articulate technical solutions to engineers and non-engineers alike.

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