Senior Data Engineer - Trading Analytics

The Quant Trading team is responsible for trading and managing risks associated with different crypto products, including spots and derivatives. The team develops and implements trading strategies in fast-paced and complex trading environments.

We are seeking a Senior Data Engineer with deep expertise in ClickHouse and AWS infrastructure to join our dynamic Trading Analytics team. This role will be crucial in supporting our data engineering needs across various trading, middle office, and trade capture systems. The ideal candidate will have a strong background in Python for ETL, AWS cloud infrastructure, and experience with data orchestration tools such as Airflow and Kafka. Experience in trading, crypto, or middle office environments is highly valued.

1. Design, implement, and manage scalable ClickHouse infrastructure for large datasets, ensuring optimal performance, availability, and maintainability.
2. Develop robust, scalable ETL pipelines using Python to handle data ingestion, transformation, and storage.
3. Collaborate with infrastructure teams to ensure proper AWS setup, covering everything from EC2, S3, RDS, Lambda, and more.
4. Build and maintain data orchestration workflows using Airflow and integrate Kafka for real-time data streaming and processing.
5. Work closely with cross-functional teams, including trading, risk management, and middle office, to ensure the data infrastructure supports all business needs.
6. Optimize performance and scalability of data pipelines, ensuring data integrity and accuracy.
7. Monitor and troubleshoot data infrastructure, implementing best practices for data governance and security.
8. Mentor junior engineers and provide technical leadership within the team.

1. 8+ years of experience in data engineering, with a focus on building and managing large-scale data systems.
2. Strong hands-on experience with ClickHouse, both in infrastructure setup and operational use.
3. Proficiency in Python, especially for building ETL pipelines and data workflows.
4. Deep understanding of AWS infrastructure, including networking, storage, compute, and security.
5. Experience with data orchestration and workflow automation using Airflow.
6. Familiarity with Kafka for building real-time data pipelines.
7. Exposure to trading, crypto, middle office, or trade capture/trade matching systems is a significant plus.
8. Experience or knowledge in machine learning and AI is a bonus.
9. Strong problem-solving skills, attention to detail, and the ability to work under pressure in a fast-paced environment.

1. Experience in financial services, particularly in trading or crypto environments.
2. Ability to work with diverse stakeholders to gather requirements and deliver solutions that meet business needs.
3. Familiarity with database optimization, query performance tuning, and monitoring tools.