Key Responsibilities :

- Own the full data delivery lifecycle: procurement, vendor discussions, process setup, pipeline design and deployment (with logging and alerting), and database insertion - optimising throughout for minimal delivery latency.

- Build internal applications that simplify how quantitative developers query and consume data.

- Work across multiple datasets to deliver standardised, consistent data outputs.

- Break down large, ambiguous problems into scoped deliverables that hold up against deadlines.

- Translate business requirements into technical specifications, and clarify technical detail back to non-technical stakeholders.

- Separate genuine user needs from stated wants to prioritise effectively.

- Propose new ideas and improvements proactively, rather than waiting on direction.

- Step into senior-level responsibilities quickly when needed to support the team.

- Follow safe, disciplined data-handling practices throughout.

Skills & Experience :

Essential :

- Strong command of Python, Bash, and SQL in a Linux environment.

- Working understanding of low-level system design for efficient data delivery applications.

- Ability to explain technical concepts clearly to non-technical stakeholders.

- Hands-on experience with ClickHouse, including its Python, Bash, and C++ integrations.

- Familiarity with Jira and Agile ways of working.

- Proficiency with Git and standard version-control workflows.

- Comfortable developing over SSH.

- Solid technical grasp of market, alternative, and supporting datasets.

- Experience leading a team of 4 or more, delivering robust data solutions end-to-end.

Ideal :

- Experience handling 1+ TB of daily data processing.

- Track record building highly efficient, resource-optimised data pipelines.

- Current with hardware and software trends relevant to data engineering.

- Writes efficient, maintainable code without relying on LLM tooling.

- Prior experience in a fast-paced, high-availability proprietary trading environment.