KDB Development Lead

Millennium is a global, diversified alternative investment firm, founded in 1989. Defined by evolution, innovation and focus, Millennium’s mission is to deliver results for our investors.

Millennium is a global, diversified alternative investment firm, founded in 1989. Defined by evolution, innovation and focus, Millennium’s mission is to deliver results for our investors.

Our people are empowered with both independence and support: the autonomy to pursue ideas with conviction and the backing of a global network committed to collaboration, disciplined risk management and continuous learning. With opportunities to deepen expertise and accelerate development, talent at Millennium is equipped to adapt, evolve and build lasting impact over time. Discover how transformative growth accelerates impact.

Information Technology is central to the health and growth of Millennium’s active, multi-manager business model, which requires flexible, scalable technology and advanced proprietary systems. The KDB Development team builds and operates high-performance time-series data platforms using kdb+ and q, with a focus on the architecture, performance, reliability, and usability of real-time and historical databases. The team also supports accessible analytics interfaces, including Jupyter notebooks, and partners closely with trading, research, data, and infrastructure stakeholders.

• Lead, mentor, and develop a team of KDB/q engineers, establishing clear priorities, engineering standards, accountability, and ownership.
• Own the architecture and roadmap for kdb+ real-time and historical database platforms, including data ingestion, intraday processing, end-of-day workflows, storage, retention, recovery, and query access.
• Design and implement scalable q solutions for high-volume real-time and historical time-series data, with a focus on performance, reliability, and maintainability.
• Drive performance tuning across memory management, database partitioning and sym attributes, query patterns, indexing, process communication, and capacity planning.
• Build and maintain analyst-facing data-access tooling, including Jupyter notebook environments, q/Python integrations, reusable notebooks, and supported query libraries.
• Establish engineering best practices for code quality, automated testing, source control, CI/CD, release management, documentation, monitoring, and incident response.
• Embed data-quality controls, reconciliation processes, entitlements, auditability, and retention policies into platform design.
• Partner with trading, quantitative research, operations, data engineering, and infrastructure teams to deliver durable solutions; lead design and code reviews, production support, and continuous improvements following incidents.

• Significant experience developing and operating production systems using kdb+ and q, including the design, support, and tuning of real-time and historical database architectures.
• Expertise in real-time data ingestion, ticker plant-based or comparable streaming architectures, intraday recovery, end-of-day processing, and historical data management.
• Strong command of time-series data design, high-performance q queries, partitioned databases, memory management, and operational performance troubleshooting.
• Experience delivering analytical workflows through Jupyter notebooks, including q/Python interoperability and well-governed self-service data access.
• Demonstrated technical leadership and experience guiding engineers through delivery as a people manager, team lead, or senior technical lead.
• Strong software engineering discipline, including testing, code review, CI/CD, version control, and production release practices.
• Experience…