Senior KDB+ Developer

Design, develop, and maintain kdb+ tick systems, with a strong understanding of data organisation, schema design, and the performance implications of different architectural approaches.

Build and operate solutions handling large scale, high frequency datasets, ensuring low latency, high throughput, and efficient memory usage.

Analyse and optimise q queries, data models, and ingestion pipelines for both real time and historical workloads.

Collaborate closely with Risk function teams to translate business requirements into efficient, scalable, and performant kdb+ solutions.

Take ownership of performance diagnostics, including CPU, memory, disk I/O, and network considerations across kdb+ processes.

Develop robust and reusable q libraries, utilities, and frameworks with a strong focus on clean, maintainable, and performant code.

Drive continuous improvement through refactoring, performance benchmarking, and adoption of best practices.

Mentor and guide junior and mid-level developers, fostering a culture of technical excellence, code quality, and knowledge sharing.

Participate in design reviews, production support, and root cause analysis of complex system issues.

Work collaboratively within an Agile or iterative delivery environment, contributing to design, implementation, testing, and release phases

8+ years of hands on experience in kdb+ development in a production environment.

Strong expertise in q language, including:

Table design (splayed, partitioned, segmented)

In memory vs on disk trade offs

Efficient joins, aggregations, and windowed analytics

Deep understanding of kdb+ tick architecture, including ticker plant, RDB, HDB, and associated patterns.

Proven experience working with large datasets and optimising queries for performance and scalability.

Strong background in Unix/Linux environments, including shell scripting for automation, monitoring, and operational tooling.

Solid understanding of software delivery processes and methodologies (Agile, CI/CD, version control, release management).

Ability to communicate clearly with both technical and non-technical stakeholders, demonstrating systematic reasoning and problem solving skills.

Knowledge of inter process communication mechanisms in kdb+ and integration with external systems.

Experience tuning kdb+ systems for low latency and high availability.

Familiarity with data quality checks, validation frameworks, and operational resilience patterns.

Exposure to financial markets data (e.g. market data, trading, risk, or post trade workflows, equity asset class).