Intermediate Quality Analyst at Citi

Mississauga, Ontario, Canada -

Full Time

Start Date

Immediate

Expiry Date

02 Mar, 26

Salary

0.0

Posted On

02 Dec, 25

Experience

2 year(s) or above

Remote Job

Yes

Telecommute

Yes

Sponsor Visa

Skills

Data Quality, Data Validation, Issue Resolution, Data Governance, Continuous Integration, Root Cause Analysis, Regulatory Compliance, Cloud Optimization, Anomaly Detection, User Acceptance Testing, Java, Python, SQL, Analytical Skills, Troubleshooting, DevOps

Industry

Financial Services

Description

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. 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 is a plus. 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. ------------------------------------------------------ Job Family Group: Technology ------------------------------------------------------ Job Family: Applications Development ------------------------------------------------------ Time Type: Full time ------------------------------------------------------ ------------------------------------------------------ For complementary skills, please see above and/or contact the recruiter. ------------------------------------------------------

Responsibilities

The Intermediate Quality Analyst will design, develop, and implement automated data quality checks for trading data, while monitoring and validating data pipelines. They will also partner with various teams to identify and resolve data anomalies and ensure compliance with regulations.