KDB Specialist

We are seeking an experienced KDB+ Developer with strong hands-on expertise in KDB+/q and time-series data processing. The ideal candidate will have demonstrated experience working with high-performance, Real Time data systems within financial services preferably in environments such as trading, risk, or market data platforms. Experience in KDB is the primary qualification for this role.The role involves designing, developing, optimizing, and supporting KDB+ systems used for Real Time analytics, quantitative research, and time-series data storage and retrieve.

Key Responsibilities

• Design, develop, and maintain KDB+/q applications for Real Time and historical data processing.
• Build and optimize high-performance, in-memory, time-series databases to support trading, analytics, and risk systems.
• Implement data ingestion pipelines for market data, trade data, quotes, and other time-series feeds.
• Develop fast and efficient q queries, scripts, and analytics to support trading desks and quantitative teams.
• Collaborate with quants, traders, data engineers, and technology teams to deliver low-latency solutions.
• Trouble shoot, optimize, and improve existing KDB+ systems for performance, memory usage, parallelization, and scalability.
• Work with Real Time streaming systems and support high-frequency trading (HFT), surveillance, P&L reporting, and analytics platforms.
• Support the adoption or integration of KDB Insights or distributed KX technologies where required.

Required Skills & Experience

• Strong hands-on experience with KDB+ and the q programming language (this is the key requirement).
• Proven experience working with time-series data, ideally in banking, trading, hedge funds, or capital markets.
• Deep understanding of columnar data storage, Real Time processing, and in-memory analytics.
• Experience building systems for:
• High-Frequency Trading (HFT)
• Risk management and Real Time risk calculations
• Quant research and analytics
• Market data processing
• Surveillance/fraud monitoring
• P&L or trading analytics
• Ability to work with large, complex datasets (real-time + historical).
• Strong debugging, optimization, and performance-tuning skills.
• Knowledge of Unix/Linux environments and scripting.