office environments within financial services. Familiarity with market data feeds (e.g., Bloomberg, Reuters, FIX) and tick-level data processing. Knowledge of SQL and experience with time-series databases (e.g., kdb+, TimescaleDB, or similar). Exposure to distributed systems, messaging frameworks (e.g., Kafka, ZeroMQ), and event-driven architectures. Excellent communication skills and ability to work effectively across quant, trading, and More ❯
office environments within financial services. Familiarity with market data feeds (e.g., Bloomberg, Reuters, FIX) and tick-level data processing. Knowledge of SQL and experience with time-series databases (e.g., kdb+, TimescaleDB, or similar). Exposure to distributed systems, messaging frameworks (e.g., Kafka, ZeroMQ), and event-driven architectures. Excellent communication skills and ability to work effectively across quant, trading, and More ❯
risk fundamentals. Minimum of 3 years' experience in a quantitative or trading development role. Hands-on, delivery-focused mindset with the ability to operate independently. Experience with Python or KDB+/Q is beneficial but not essential. Stable career track record and a genuine interest in working closely with trading teams. This is a high-visibility position within the More ❯
scripting experience (Python or Bash) Proven track record in managing technical delivery and cross-functional collaboration Understanding of front-to-back trade flow and system architecture Exposure to microservices, kdb+/q, or data-intensive systems is an advantage Familiarity with Confluence, Jira, and structured project tracking Excellent analytical, organisational, and stakeholder management skills This role suits a technically More ❯
The Kdb database, is widely used in the financial services industry, particularly by major investment banks, for high-speed, Real Time data processing and analytics. Kdb+ is a high-performance, column-based, in-memory database optimized for time-series data analysis, commonly used in financial services for handling large Real Time and historical datasets. It is developed and uses … the q programming language, which is designed for high-speed data manipulation. 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 … 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. More ❯
