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, testing automation, and governance frameworks. You will work closely with trading technology teams, quants, risk management, and data engineering to implement automated data quality solutions that ensure high-fidelity financial data for decision-making and regulatory compliance.
Your work will directly impact the bank’s ability to execute trades effectively, manage risk efficiently, and comply with financial regulations globally.
Key Responsibilities:
- Develop and implement automated data quality checks for real-time and batch trading data.
- 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:
- At least 5 years of experience in Data Quality Engineering, Data Governance, or Data Testing within a global banking or capital markets environment.
- Strong experience in automation using Java for Backend testing, API testing and UI automation with Selenium.
- Hands-on experience in automation/tooling using Python
- Proficiency in SQL for data validation and querying large datasets.
- Experience embedding data quality tests in DevOps CI/CD pipelines.
- Experience working in AWS, Azure, or GCP data services.
- Strong analytical and troubleshooting skills for debugging data quality issues.
- Ability to work in a fast-paced trading environment with cross-functional teams.
- Strong understanding of trading data structures, market data, and financial instruments across asset classes (Equities, Fixed Income, FX, Derivatives, Commodities).
- Knowledge of risk metrics and trade lifecycle processes in investment banking.
- Experience with data quality tools (such as Great Expectations, Monte Carlo, Talend, Collibra, Informatica DQ) is a plus.
- Experience with big data platforms (such as Snowflake, Databricks, Spark, Hadoop) is a plus.
- Experience with data pipeline orchestration tools (such as Airflow, DBT, Prefect) is a plus.
Preferred Qualifications:
- Degree in Computer Science, Software/Computer Engineering, or a related field.
- Experience with real-time market data validation and anomaly detection.
- Experience in AI/ML-driven anomaly detection for trading and risk data quality.
Why Join Us?
- Work on high-impact financial data pipelines powering global trading operations.
- Collaborate with top-tier engineers, quants, and traders in a cutting-edge financial environment.
- Gain exposure to AI-driven data validation and anomaly detection in real-time markets.
- Be part of a global financial institution with opportunities for career growth and leadership development.
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Job Family Group:
Technology
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Job Family:
Technology Quality
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Time Type:
Full time
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