Senior KDB+/q Engineer (Finance/Trading)

About the Role

We are seeking a Senior KDB+/q Engineer to lead the design, development, and optimization of high-performance data systems in a trading/financial environment. This role requires a strong blend of leadership and hands-on expertise from architecture and system design to coding, configuration, and performance tuning. Experience in electronic trading, market data, or financial analytics is required.

Responsibilities

• Architecture & Design: Lead the design and development of scalable KDB+/q solutions to support trading systems, market data pipelines, and analytics platforms.
• Hands-On Development: Write, optimize, and maintain production-grade q code for real-time and historical data analysis.
• System Integration: Configure and integrate KDB+/q with trading applications, risk engines, and downstream analytics tools.
• Performance Tuning: Ensure ultra-low-latency and high-throughput processing of large volumes of tick and transactional data.
• Leadership: Provide technical direction to engineers, mentor junior developers, and collaborate with cross-functional teams (traders, quants, data scientists).
• AI/ML Collaboration: Partner with data science teams to integrate AI/ML models into trading workflows, enhancing predictive analytics and decision support.
• Best Practices: Establish coding standards, CI/CD pipelines, and monitoring frameworks for reliability and scalability.

Requirements

• Strong KDB+/q expertise: 5+ years of hands-on development experience with KDB+/q in financial markets.
• Finance/Trading background: Direct experience with equities, fixed income, FX, derivatives, or related trading environments.
• Architecture & leadership: Proven ability to design scalable data systems and provide technical leadership to teams.
• Hands-on mindset: Comfortable coding, debugging, configuring, and optimizing production systems.
• Integration skills: Knowledge of APIs, messaging systems (Kafka, Solace, or similar), and market data feeds.
• AI/ML exposure (plus): Experience collaborating with AI/ML teams or integrating models into production pipelines.
• Other technical skills (preferred): Python, C++, Linux, distributed systems, or cloud platforms (AWS/Google Cloud Platform/Azure).
• Strong communication skills and ability to work closely with trading and quantitative research teams.

Nice to Have

• Experience with time-series databases beyond KDB+ (InfluxDB, TimescaleDB).
• Familiarity with regulatory reporting and compliance in financial services.
• Contributions to open-source projects or AI/ML frameworks.