Senior KDB+ Developer

Overview

Senior KDB+ Developer to design, build and optimize high-performance data platforms based on kdb+. You will work closely with Risk teams to translate requirements into scalable, low-latency solutions. You will optimize q queries, data models, and ingestion pipelines for real-time and historical workloads. You will mentor juniors, participate in design reviews, and drive continuous improvement in an agile environment. This role offers impact on risk analytics and large-scale data systems in a production setting.

Responsibilities

• Design, develop, and maintain kdb+ tick systems with attention to data organization and architecture.
• Handle large-scale, high-frequency datasets ensuring low latency, high throughput, and efficient memory usage.
• Analyze and optimize q queries, data models, and ingestion pipelines for real-time and historical workloads.
• Collaborate with Risk function teams to translate business needs into scalable, performant code.
• Drive refactoring, benchmarking, and adoption of best practices for performance.
• Mentor junior and mid-level developers to promote technical excellence and knowledge sharing.
• Participate in design reviews, production support, and root cause analysis of complex issues.
• Contribute to Agile or iterative delivery processes across design, implementation, testing and release phases.

Key requirements

• 8+ years of hands-on kdb+ development in production.
• Strong q language expertise: table design (splayed, partitioned, segmented), in-memory vs on-disk trade-offs, efficient joins, aggregation, windowed analytics.
• Deep understanding of kdb+ tick architecture (ticker plant, RDB, HDB) and related patterns.
• Experience with large datasets and optimizing queries for performance and scalability.
• Proficiency in Unix/Linux and shell scripting for automation and tooling.
• Solid understanding of Agile, CI/CD, version control, and release processes.
• Clear communication with both technical and non-technical stakeholders.
• strong communication and stakeholder management
• problem solving and systematic reasoning
• mentoring and knowledge sharing
• kdb+ development in production environments
• q language expertise (table design, in-memory vs on-disk, joins, aggregation, windows)
• kdb+ tick architecture (ticker plant, RDB, HDB)

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