Accolite - KDB Lead

Description :

About the job :

Required Skills & Qualifications :

- 7+ years of experience in building high-performance data systems using kdb+/q.

- Strong expertise in time-series data modeling, tick data architecture, and real-time analytics.

- Experience leading teams or large-scale projects.

- Solid understanding of Linux systems, networking, and data caching.

- Familiarity with Python, Java, or C++ for integration and tooling.

- Experience with Kafka, AWS, Spark, or similar technologies is a plus.

- Bachelors or Masters degree in Computer Science, Engineering, Mathematics, or related field.

Key Responsibilities :

- Lead end-to-end design and development of kdb+/q-based data systems for real-time and historical market data.

- Architect scalable data pipelines to support analytics, trading, and risk systems.

- Collaborate with stakeholders including trading, quant, and technology teams to identify data requirements and optimize workflows.

- Manage a team of KDB developers, providing technical direction, mentorship, and code reviews.

- Oversee data ingestion, normalization, and query optimization for large-scale time-series data.

- Ensure data quality, performance tuning, and system resilience using best practices.

- Integrate KDB systems with Python, Java, or other analytics and visualization tools.

- Develop monitoring and alerting solutions for KDB environments.

- Stay current with KDB+/q enhancements, industry trends, and performance optimization techniques.

Preferred/Good To Have :

- Experience in investment banking, asset management, or capital markets environments.

- Strong problem-solving and analytical skills.

- Excellent communication and stakeholder management skills.

Desired Skills and Experience :

- kdb+, q Programming, Time-Series Data, Real-Time Analytics, Tick Data Architecture, Data Engineering, Market Data Systems, Capital Markets Technology, Linux, Performance Tuning, Query Optimization, Data Pipelines, Python Integration, Java Integration, C++ Integration, Kafka, AWS, Spark, Monitoring and Alerting, System Architecture, Technical Leadership