Test Data Management Consultant

Test Data Management Consultant Location: Chicago, IL (Hybrid - 3 days onsite a week) Duration: 12-24+ months Contract Role Summary We are seeking a Test Data Management (TDM) Consultant with strong expertise in QA architecture, data analytics, and AI-driven testing solutions. This role will support client's mission-critical platforms by ensuring high-quality, compliant, and scalable test data strategies across clearing, risk, and financial systems. You will play a key role in enabling testing for complex platforms such as margin calculation engines, trade processing systems, and risk analytics frameworks. Key Responsibilities Test Data Strategy for Financial Systems Design and implement enterprise TDM strategies for derivatives clearing and risk systems Develop solutions for: Data masking (PII & sensitive financial data) Data subsetting for large transactional datasets Synthetic data generation for rare market scenarios Ensure compliance with SEC, CFTC, and internal risk governance standards QA Architecture & Testing Enablement Build and support data-driven testing frameworks for: Margin calculations (e.g., STANS) Trade lifecycle processing Market stress testing scenarios Integrate TDM with automation frameworks and CI/CD pipelines Enable testing across high-volume, low-latency systems Data Analysis & Financial Modeling Support Analyze complex datasets related to: Options pricing Risk exposure Clearing and settlement Identify data gaps impacting test coverage and risk validation Partner with Quant, Risk, and Data teams to align datasets with real-world market conditions AI & Advanced Automation Apply AI/ML techniques to: Generate synthetic market and trade data Detect anomalies in risk and pricing datasets Optimize test coverage using predictive analytics Explore use of Generative AI for test case and data generation Cross-Functional Collaboration Work with QA, Quantitative Analysts, Risk Management, Data Engineering, and DevOps teams Support integration across data platforms, APIs, and risk engines Contribute to enterprise initiatives around data governance and modernization Required Skills & Qualifications QA Architecture & Engineering 8+ years in QA/Test Engineering, with strong architecture experience Experience testing financial systems or high-volume transaction platforms Strong knowledge of automation tools (Selenium, REST Assured, Cypress, etc.) Test Data Management Expertise Hands-on experience with TDM tools (e.g., Delphix, Informatica TDM) Deep expertise in: Data masking (especially financial/PII data) Data provisioning and subsetting Synthetic data generation Data & Analytics Strong SQL and data analysis skills Experience with large-scale data platforms and ETL pipelines Familiarity with tools such as Talend, Snowflake, or similar AI / ML Knowledge Working knowledge of AI/ML concepts applied to QA and data Experience with AI-driven testing or data generation tools Understanding of Generative AI applications in testing Domain Expertise (Highly Preferred) Experience in capital markets, derivatives, or clearing systems Familiarity with: Options lifecycle Risk and margin models (e.g., STANS) Understanding of regulatory environments (SEC, CFTC) Nice to Have Experience with cloud platforms (AWS, Azure) Knowledge of data governance frameworks and audit requirements Exposure to DevOps / CI-CD pipelines Experience in Agile / SAFe environments Key Traits: Strong analytical mindset with attention to detail Ability to operate in highly regulated, mission-critical environments Strong collaboration across technical and business teams Passion for leveraging AI to transform QA and data practices