Senior Data Quality Assurance Engineer
Senior Data Quality Assurance Engineer
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Job Description
Role: Senior Data Quality Assurance Engineer
Location: New York NY ONLY LOCAL
NOTE: ONLY W2 AND THE INTERVIEW WILL SINGLE ROUND ONLY & WE HAVE INTERVIEW SLOTS ON FRIDAY AND MONDAY (10 TO 1PM EST)
Responsibilities
The Senior Data Quality Assurance Engineer will be responsible for ensuring the accuracy integrity and consistency of data across our systems. This role involves designing and implementing quality frameworks conducting data quality assessments and performing advanced statistical validations. The ideal candidate will leverage AI/ML techniques to detect patterns and anomalies in financial and investment data. Additionally this position focuses on automating data quality processes to uphold robust data governance and ensure compliance with industry regulations.
- Lead the design and implementation of quantitative data quality frameworks including statistical checks and anomaly detection systems.
- Utilize advanced statistical methods (e.g. linear and nonlinear modelling Bayesian analysis) to evaluate data quality across large complex datasets.
- Develop and integrate AI/ML models for predictive data quality checks and to improve data accuracy over time. Improvement in data collection
- Ensure compliance with financial regulations and industry standards related to data governance including managing data privacy and security risks.
- Mentor junior quantitative analysts promoting best practices in data quality management and statistical analysis.
- Communicate findings data quality trends and proposed solutions to senior leadership ensuring datadriven decisionmaking.
- Lead the creation and maintenance of automated test scripts to improve test efficiency.
- Ensure continuous integration of automated tests into the CI/CD pipeline.
- Identify gaps in testing coverage and propose solutions.
Requirements
- Statistical Expertise: Advanced knowledge of statistical methods including linear/nonlinear modelling hypothesis testing and Bayesian techniques.
- AI/ML Integration: Strong skills in applying AI/ML algorithms (e.g. neural networks random forest anomaly detection) for data quality checks and predictive analysis. Experience with cloudbased environments (AWS Azure etc.).
- Quantitative Finance: Deep understanding of financial instruments market data and the use of quantitative methods in portfolio management and risk analysis.
- Programming Skills: Proficiency in statistical programming languages (Python R SQL) and experience with tools like MATLAB SAS or similar platforms.
- Automation: Experience in developing and implementing automated data validation processes including realtime monitoring and alert systems.
- Data Governance: Strong knowledge of data management principles regulatory compliance and data governance practices particularly in the context of financial services.
- Leadership & Mentorship: Ability to mentor and guide junior team members sharing expertise in statistical analysis AI/ML and data quality best practices.
- Problem Solving: Excellent analytical skills to identify root causes of data quality issues and implement longterm solutions.
- Collaboration: Strong ability to work with crossfunctional teams including data scientists engineers and financial experts to enhance overall data quality.
Mike
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Employment Type
Full Time
