Citi, the leading global bank, has approximately 200 million customer accounts and does business in more than 160 countries and jurisdictions. Our core activities are safeguarding assets, lending money, making payments and accessing the capital markets on behalf of our clients.
Citi’s Mission and Value Proposition explain what we do and Strategy explain how we do it. Our mission is to serve as a trusted partner to our clients by responsibly providing financial services that enable growth and economic progress. We strive to earn and maintain our clients’ and the public’s trust by constantly adhering to the highest ethical standards and making a positive impact on the communities we serve.
As a Software Development Engineer in Test (SDET) specializing in Data Quality within the Global Markets division of a leading investment bank, you will be instrumental in ensuring the integrity, accuracy, and consistency of critical financial data across trading, risk management, and compliance systems.
This role demands a highly technical mindset, combining robust hands-on skills in data validation with expertise in test automation. You will collaborate closely with trading technology teams, quantitative analysts, risk management professionals, and data engineers. Your primary objective will be to design, develop, and implement sophisticated data quality solutions that guarantee high-fidelity financial data, essential for informed decision-making, operational efficiency, and stringent regulatory compliance.
Your contributions will directly enhance the bank’s capacity to execute trades seamlessly, manage risk effectively, and adhere to global financial regulations.

REQUIRED SKILLS & QUALIFICATIONS

• Experience: Minimum of 3+years of experience in Quality Assurance, with a strong focus on data quality in backend testing.
• Backend & API Automation: Strong experience in test automation using Java for backend systems and API testing.
• Python for Tooling: Hands-on experience in developing automation scripts using Python.
• SQL Proficiency: Proficiency in SQL for complex data validation, querying large datasets, and data manipulation.
• Analytical & Troubleshooting Skills: Exceptional analytical and troubleshooting skills, particularly for debugging and resolving intricate data quality issues.
• DevOps Integration: Demonstrated experience embedding data quality tests and automation within DevOps CI/CD pipelines.
• Adaptability: Ability to thrive and contribute effectively in a dynamic, fast-paced trading environment with cross-functional teams.

EDUCATION:

Bachelor’s degree/University degree or equivalent experience
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MOST RELEVANT SKILLS

Please see the requirements listed above.
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OTHER RELEVANT SKILLS

For complementary skills, please see above and/or contact the recruiter.
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Citi is an equal opportunity employer, and qualified candidates will receive consideration without regard to their race, color, religion, sex, sexual orientation, gender identity, national origin, disability, status as a protected veteran, or any other characteristic protected by law.
If you are a person with a disability and need a reasonable accommodation to use our search tools and/or apply for a career opportunity review Accessibility at Citi.
View Citi’s EEO Policy Statement and the Know Your Rights poster

• Automated Data Quality Development: Design, develop, and implement automated data quality checks for both real-time and batch processing of trading data.
• Data Pipeline Validation: Monitor and rigorously validate data pipelines supporting trade execution, pricing models, risk analytics, and post-trade settlement processes.
• Issue Identification & Resolution: Partner with trading desks, quantitative teams, and data engineers to proactively identify, analyze, and resolve complex data anomalies.
• Data Governance & Traceability: Build and maintain solutions for data profiling, lineage tracking, and metadata management to ensure comprehensive data traceability and auditability.
• Continuous Integration for Data Reliability: Integrate data validation rules and automated tests into Continuous Integration/Continuous Delivery (CI/CD) pipelines.
• Root Cause Analysis: Conduct thorough root cause analysis for identified data quality issues and drive the implementation of effective corrective and preventative actions.
• Regulatory Compliance: Ensure all data quality processes and solutions adhere to global financial regulations and internal compliance standards.
• Cloud Environment Optimization: Collaborate with DevOps and Cloud Engineering teams to optimize and scale data quality solutions within cloud-based environments (e.g., AWS, Azure, GCP).
• Advanced Anomaly Detection: Leverage and integrate AI/Machine Learning-based anomaly detection models to proactively identify subtle and complex data inconsistencies.
• UAT and Product Rollout Support: Provide crucial support for User Acceptance Testing (UAT) processes and the successful rollout of products into production environments, ensuring data quality readiness.