KDB/q Tech Lead for Real-Time Time-Series

Millennium Management LLC; New York (NY); On-site; USD 175,000 - 250,000; Full time

Job summary

Millennium is seeking a KDB Development Lead to guide a team of engineers responsible for real-time and historical time-series data platforms. You will own the architecture, roadmap, and delivery of scalable kdb+ solutions, focusing on performance, reliability, and analytics tooling.

The role requires strong leadership, hands-on KDB/q expertise, and the ability to partner with trading, research, and data teams to drive durable data platforms in a fast-paced environment.

Qualifications

• Significant experience developing and operating production systems using kdb+ and q.
• Experience with real-time data ingestion and time-series architectures.
• Strong leadership and ability to guide engineers through delivery.

Responsibilities

• Lead, mentor, and develop a team of KDB/q engineers with clear priorities and standards.
• Own architecture and roadmap for kdb+ platforms including ingestion, processing, storage and recovery.
• Design scalable q solutions for high-volume data with focus on performance and reliability.
• Drive performance tuning across memory management, partitioning, and indexing.
• Build and maintain analyst-facing data-access tooling including Jupyter notebook environments.
• Establish engineering best practices for testing, CI/CD, and release management.
• Embed data-quality controls and retention policies into platform design.
• Collaborate with trading, research, data, and infra teams to deliver durable solutions.

Skills

KDB+/Q

Production systems

Time-series data

Jupyter notebooks

Leadership

Python interoperability

Strong communication

CI/CD

Tools

Python

Java

C++

Kafka

Solace

KDB

Git

Job description

Millennium is seeking a KDB Development Lead to guide a team of engineers responsible for real-time and historical time-series data platforms. You will own the architecture, roadmap, and delivery of scalable kdb+ solutions, focusing on performance, reliability, and analytics tooling.

The role requires strong leadership, hands-on KDB/q expertise, and the ability to partner with trading, research, and data teams to drive durable data platforms in a fast-paced environment.