Website:
khawk.com
Job details:
Role Overview:
We are seeking a Quant Data Engineer with deep expertise in ClickHouse to build and scale our core data infrastructure. This role is central to enabling low-latency analytics, robust data pipelines, and high-performance research and trading systems.
You will work closely with portfolio managers, quantitative researchers, and engineers to ensure data is accurate, scalable, and accessible for real-time and historical analysis.
Key Responsibilities:
Data Architecture & ClickHouse
- Design, build, and maintain ClickHouse clusters for large-scale financial time-series data
- Optimize schemas for high-performance analytical queries
- Tune query performance, partitioning, and indexing strategies
- Manage real-time and batch ingestion pipelines
- Monitor and improve system performance and reliability
Data Engineering & Pipelines
- Develop robust ETL/ELT pipelines for market and alternative data
- Process high-frequency datasets (tick, trades, order book)
- Ensure data quality, validation, and consistency
Quant & Trading Support
- Partner with quantitative researchers to deliver structured datasets
- Enable efficient backtesting and research workflows
- Optimize data access for trading systems
Systems & Performance
- Ensure low-latency data availability
- Implement monitoring, alerting, and fault tolerance
- Continuously improve scalability and system reliability
Required Qualifications:
- 4+ years experience in data engineering or related field
- Strong hands-on experience with ClickHouse in production (required)
- Advanced proficiency in Python and SQL
- Experience with time-series data and high-volume data pipelines
- Familiarity with Kafka (or similar), Airflow/Prefect, and cloud platforms (AWS/GCP/Azure)
Preferred Qualifications:
- Experience in hedge funds, trading firms, or financial data platforms
- Understanding of market microstructure and order book data
- Experience optimizing analytical databases at scale
- Exposure to low-latency or real-time systems
- Ideal Candidate
- Deep expertise in analytical databases (especially ClickHouse)
- Strong systems thinker focused on performance and scalability
- Comfortable working with large, real-time datasets
- Collaborative and able to work across quant, trading, and engineering teams
- Compensation
- Competitive base salary
- Performance-based bonus
- Comprehensive benefits
How to Apply:
Please submit:
- Resume
- Relevant project or GitHub work (if available)
- Brief summary of your ClickHouse experience (if available)
Click on Apply to know more.