Senior Quantitative Data Engineer

As a Senior Quantitative Data Engineer, you will play a crucial role in supporting and enhancing the automated trading infrastructure of the company. Your responsibilities will involve designing, developing, and maintaining robust data pipelines and ETL workflows, building tools for data onboarding, validation, reconciliation, and monitoring, as well as optimizing database schemas and data access patterns. You will also be responsible for ensuring the accuracy, completeness, and consistency of datasets used in research and live trading, developing automated data quality checks, and supporting researchers in cleaning and enriching datasets. Key Responsibilities: - Design, develop, and maintain robust data pipelines and ETL workflows. - Build tools for data onboarding, validation, reconciliation, and monitoring. - Drive automation to eliminate manual operational processes. - Ensure accuracy, completeness, and consistency of datasets used in research and live trading. - Develop automated data quality checks and anomaly detection frameworks. - Investigate and resolve discrepancies across multiple data sources. - Own and proactively monitor production data pipelines and critical trading processes. - Drive improvements in data infrastructure, scalability, and operational efficiency. - Partner with quantitative researchers, traders, and software engineers to deliver reliable solutions. - Mentor junior engineers and contribute to technical excellence across the team. Qualifications Required: - 5+ years of experience in data engineering. - Strong Python programming skills and experience with Pandas, Polars, NumPy, and PyArrow. - Expertise in SQL (PostgreSQL, MySQL, MSSQL) and database design. - Strong Linux and shell scripting skills. - Experience designing and maintaining ETL and data processing pipelines. - Excellent debugging and root-cause analysis skills. - Strong communication and collaboration skills. - Ability to work effectively in a fast-paced, live trading environment. This role offers you the prospect to work on mission-critical automated trading systems, high ownership, exposure to quantitative research and live trading operations, a fast-paced environment with a direct impact on business outcomes, and the opportunity to mentor others and shape the evolution of the firm's data infrastructure. As a Senior Quantitative Data Engineer, you will play a crucial role in supporting and enhancing the automated trading infrastructure of the company. Your responsibilities will involve designing, developing, and maintaining robust data pipelines and ETL workflows, building tools for data onboarding, validation, reconciliation, and monitoring, as well as optimizing database schemas and data access patterns. You will also be responsible for ensuring the accuracy, completeness, and consistency of datasets used in research and live trading, developing automated data quality checks, and supporting researchers in cleaning and enriching datasets. Key Responsibilities: - Design, develop, and maintain robust data pipelines and ETL workflows. - Build tools for data onboarding, validation, reconciliation, and monitoring. - Drive automation to eliminate manual operational processes. - Ensure accuracy, completeness, and consistency of datasets used in research and live trading. - Develop automated data quality checks and anomaly detection frameworks. - Investigate and resolve discrepancies across multiple data sources. - Own and proactively monitor production data pipelines and critical trading processes. - Drive improvements in data infrastructure, scalability, and operational efficiency. - Partner with quantitative researchers, traders, and software engineers to deliver reliable solutions. - Mentor junior engineers and contribute to technical excellence across the team. Qualifications Required: - 5+ years of experience in data engineering. - Strong Python programming skills and experience with Pandas, Polars, NumPy, and PyArrow. - Expertise in SQL (PostgreSQL, MySQL, MSSQL) and database design. - Strong Linux and shell scripting skills. - Experience designing and maintaining ETL and data processing pipelines. - Excellent debugging and root-cause analysis skills. - Strong communication and collaboration skills. - Ability to work effectively in a fast-paced, live trading environment. This role offers you the prospect to work on mission-critical automated trading systems, high ownership, exposure to quantitative research and live trading operations, a fast-paced environment with a direct impact on business outcomes, and the opportunity to mentor others and shape the evolution of the firm's data infrastructure.