Intermediate Quality Analyst

• Design, develop, and implement automated data quality checks for both real-time and batch processing of trading data
• monitor and rigorously validate data pipelines supporting trade execution, pricing models, risk analytics, and post-trade settlement processes
• proactively identify, analyze, and resolve complex data anomalies
• build and maintain solutions for data profiling, lineage tracking, and metadata management
• integrate data validation rules and automated tests into CI/CD pipelines
• conduct thorough root cause analysis for identified data quality issues
• ensure all data quality processes and solutions adhere to global financial regulations and internal compliance standards
• collaborate with DevOps and Cloud Engineering teams to optimize and scale data quality solutions within cloud-based environments
• leverage and integrate AI/Machine Learning-based anomaly detection models to identify subtle and complex data inconsistencies
• provide support for User Acceptance Testing (UAT) processes and successful rollout of products into production environments.

• Minimum of 3+ years of experience in Quality Assurance, with a strong focus on data quality in backend testing
• strong experience in test automation using Java for backend systems and API testing
• hands-on experience in developing automation scripts using Python
• proficiency in SQL for complex data validation, querying large datasets, and data manipulation
• exceptional analytical and troubleshooting skills, particularly for debugging and resolving intricate data quality issues
• demonstrated experience embedding data quality tests and automation within DevOps CI/CD pipelines
• ability to thrive and contribute effectively in a dynamic, fast-paced trading environment with cross-functional teams.

AI/Machine Learning-based anomaly detection models

Global benefits designed to support well-being, growth, and work-life balance.