Senior KDB/Q Low-Latency Real-Time Equities Data Engineer

Madison-Davis, LLC; New York (NY); On-site; USD 160,000 - 220,000; Full time

Job summary

Madison-Davis, LLC is seeking a Senior KDB Developer to join our technology organization supporting real-time equities data and analytics. You will engineer high-performance platforms to process vast real-time and historical financial data, working with trading, quantitative, engineering, QA, and production teams.

The ideal candidate combines deep KDB/Q expertise with experience building real-time, low-latency financial data systems and will be onsite in New York City three days per week.

Qualifications

• Experience in low-latency financial data environments.
• Experience with large-scale market/time-series datasets.
• Proficiency in Python or Java.
• Strong understanding of time-series architectures and streaming data.
• Ability to collaborate with front-office stakeholders.
• Willingness to work onsite in NYC three days per week.

Responsibilities

• Design and develop low-latency KDB+/Q platforms for real-time financial data.
• Build and optimize streaming pipelines supporting market, ticker, order, and execution data.
• Develop scalable tickerplant, RDB, and HDB architectures.
• Design time-series models and high-performance query frameworks.
• Optimize platform latency, throughput, reliability, and query performance.
• Develop APIs and reusable components for trading and analytics applications.
• Implement monitoring and automated data-quality controls.
• Troubleshoot complex real-time data and production issues.

Skills

KDB+/Q

Low-latency

Time-series

Python

Java

Streaming data

Job description

Madison-Davis, LLC is seeking a Senior KDB Developer to join our technology organization supporting real-time equities data and analytics. You will engineer high-performance platforms to process vast real-time and historical financial data, working with trading, quantitative, engineering, QA, and production teams.

The ideal candidate combines deep KDB/Q expertise with experience building real-time, low-latency financial data systems and will be onsite in New York City three days per week.