Senior KDB/Q Developer

16 Minutes ago • 3-8 Years

Programming

Job Description

This role involves building a trading platform for an innovative international top-tier hedge fund. The Senior KDB/Q Developer will design, develop, and maintain KDB+/q databases and real-time data processing systems. Key responsibilities include optimizing data ingestion pipelines using Kafka, integrating KDB systems with Java applications, and supporting React-based front-end interfaces. The role also involves monitoring and tuning performance of large-scale time-series datasets, troubleshooting production issues, and partnering with quantitative researchers and traders to design new data-driven features and analytics.

Good To Have:

Experience integrating KDB with Java and Kafka for distributed data processing and messaging.
Familiarity with React-based UI systems, including API design to serve real-time data.
Experience with cloud-based infrastructure (AWS, GCP, or similar) and containerization (Docker/Kubernetes).

Must Have:

Design, develop, and maintain KDB+/q databases and real-time data processing systems.
Build and optimize data ingestion pipelines from multiple market data sources using Kafka.
Collaborate with Java developers to integrate KDB systems with trading, analytics, and risk applications.
Support React-based front-end interfaces by developing efficient APIs and query services.
Monitor and tune performance of large-scale time-series datasets for latency and throughput.
Troubleshoot production issues, ensuring high data quality, reliability, and uptime.
Partner with quantitative researchers and traders to design new data-driven features and analytics.
3-8 years of hands-on experience developing in KDB+/q in a financial environment.
Strong understanding of time-series data, market data structures, and real-time data processing.
Solid working knowledge of Linux and scripting for system monitoring and automation.
Proficiency in query optimization, data modeling, and performance tuning in KDB.
Ability to work collaboratively with engineering, quant, and trading teams.
Strong communication and problem-solving skills, with attention to detail and reliability.

Add these skills to join the top 1% applicants for this job

bloomberg

data-structures

game-texts

react

linux

aws

docker

front-end

kubernetes

java

Project description

Building a trading platform for innovative international top-tier hedge fund from the ground up, comprising of front-office system for traders, pre-trade checks and analysis, intra-day positions management, order management and routing, risks and limits management, reports of trading activities, FIX connectivity, market data providers connectivity (e.g. Bloomberg B-pipe).

Responsibilities

Design, develop, and maintain KDB+/q databases and real-time data processing systems supporting trading and research.
Build and optimize data ingestion pipelines from multiple market data sources using Kafka.
Collaborate with Java developers to integrate KDB systems with trading, analytics, and risk applications.
Support React-based front-end interfaces by developing efficient APIs and query services for visualization and analysis.
Monitor and tune performance of large-scale time-series datasets for latency and throughput.
Troubleshoot production issues, ensuring high data quality, reliability, and uptime.
Partner with quantitative researchers and traders to design new data-driven features and analytics.

Skills

Must have

3-8 years of hands-on experience developing in KDB+/q within a trading or financial environment.
Strong understanding of time-series data, market data structures, and real-time data processing.
Solid working knowledge of Linux and scripting for system monitoring and automation.
Proficiency in query optimization, data modeling, and performance tuning in KDB.
Ability to work collaboratively with engineering, quant, and trading teams in a fast-paced environment.
Strong communication and problem-solving skills, with attention to detail and reliability.

Nice to have

Experience integrating KDB with Java and Kafka for distributed data processing and messaging.
Familiarity with React-based UI systems, including API design to serve real-time data.
Experience with cloud-based infrastructure (AWS, GCP, or similar) and containerization (Docker/Kubernetes).