Senior KDB/Q Developer $$ Offline

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.

• Mandatory Skills Description:

  • 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 Skills Description:

  • 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).