Role Overview:
As a Data Quality Engineer in the Global Markets division of a leading investment bank, you will ensure the integrity, accuracy, and consistency of data across critical trading, risk, and compliance systems.
This role requires a technical mindset with strong hands-on skills in data validation and testing automation. You will work closely with trading technology teams, quants, risk management, and data engineering to implement data quality solutions that ensure high-fidelity financial data for decision-making and regulatory compliance.
Key Responsibilities:
- Develop and implement automated data quality checks for real-time and batch trading data.
- Support initiatives related to User Acceptance Testing (UAT) process and product rollout into production.
- Monitor and validate data pipelines for trade execution, pricing models, risk analytics, and post-trade settlement.
- Work with trading desks, quants, and data engineers to identify and resolve data anomalies.
- Build data profiling, lineage tracking, and metadata management solutions to ensure traceability and compliance.
- Integrate data validation rules into CI/CD pipelines, ensuring continuous data reliability in trading applications.
- Conduct root cause analysis for data quality issues and drive corrective actions.
- Ensure compliance with global financial regulations
- Collaborate with DevOps and Cloud teams to optimize data quality solutions in cloud-based environments (AWS, Azure, GCP).
- Leverage AI/ML-based anomaly detection models to proactively detect data inconsistencies.
Key Skills & Qualifications:
- Minimum 2 years of experience in Quality Assurance.
- Strong experience in automation using Java for Backend testing, API testing
- Hands-on experience in automation/tooling using Python
- Proficiency in SQL for data validation and querying large datasets.
- Strong analytical and troubleshooting skills for debugging data quality issues.
- Ability to work in a fast-paced trading environment with cross-functional teams.
- Experience embedding data quality tests in DevOps CI/CD pipelines.
- Experience working in AWS, Azure, or GCP data services is a plus.
Preferred Qualifications:
- Degree in Computer Science, Software/Computer Engineering, or a related field.
Technology Quality
Time Type:
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