KDB Specialist
Posted 7 days ago by DNS Info Ltd
Negotiable
Undetermined
Undetermined
London Area, United Kingdom
Summary: The KDB Specialist role focuses on leveraging Kdb+, a high-performance time-series database, to support data-intensive applications within capital markets. Key responsibilities include optimizing data processing for high-frequency trading, risk management, and analytics. The position requires expertise in real-time data analysis and the use of the q programming language. The role is situated in London, United Kingdom, within a fast-paced financial environment.
Key Responsibilities:
- Optimize Kdb+ for high-frequency trading and real-time analytics.
- Monitor and calculate risk exposure across portfolios.
- Develop and implement trading models and strategies using historical and real-time data.
- Analyze data streams for surveillance and fraud detection.
- Provide instant feedback on trading performance through P&L reporting.
Key Skills:
- Expertise in Kdb+ and its applications in capital markets.
- Proficiency in the q programming language.
- Strong analytical skills for real-time data processing.
- Experience with high-frequency trading and risk management.
- Ability to work with large datasets efficiently.
Salary (Rate): undetermined
City: London Area
Country: United Kingdom
Working Arrangements: undetermined
IR35 Status: undetermined
Seniority Level: undetermined
Industry: IT
Primary Use Cases Kdb+ is optimized as a high-performance time-series database, making it ideal for the demanding, data-intensive environments within capital markets. Common applications include:
- High-Frequency Trading (HFT): Processing massive volumes of market data (trades and quotes) in milliseconds to enable rapid, automated trading decisions.
- Risk Management: Calculating and monitoring risk exposure across portfolios in real time, allowing firms to quickly respond to market changes.
- Quantitative Research and Analytics: Providing a single platform for both real-time and historical data analysis, crucial for developing trading models and strategies.
- Surveillance and Fraud Detection: Analyzing data streams in real time to identify unusual patterns or potential fraudulent activities.
- Profit & Loss (P&L) Reporting: Offering instant feedback on the performance of trading positions for traders and analysts.
Key features Performance: Known for its speed, it processes and analyzes massive datasets in real-time by storing data primarily in RAM. Columnar and time-series focused: It stores data in columns, which is efficient for analytics, and is particularly strong at handling time-series data, a critical component for many financial applications. q programming language: Includes a built-in, vector-based language called "q," which is an expressive, high-performance language used for building data analytics solutions. Use cases: Widely adopted by major financial institutions for high-frequency trading, real-time analytics, and historical data storage and retrieval. Kdb Insights Database: A more recent, distributed version of kdb+ designed for scalability with features like scalable query routing and temporal storage tiering.