Senior Data Quality Assurance Engineer

Role : SeniorData Quality Assurance Engineer

Location : New York NYONLY LOCAL

NOTE : ONLY W2AND THE INTERVIEW WILL SINGLE ROUND ONLY & WE HAVE INTERVIEWSLOTS ON FRIDAY AND MONDAY (10 TO 1PM EST)

Responsibilities

The Senior DataQuality Assurance Engineer will be responsible for ensuring theaccuracy integrity and consistency of data across our systems.

Thisrole involves designing and implementing quality frameworksconducting data quality assessments and performing advancedstatistical validations.

The ideal candidate will leverage AI / MLtechniques to detect patterns and anomalies in financial andinvestment data. Additionally this position focuses on automatingdata quality processes to uphold robust data governance and ensurecompliance with industryregulations.

• Lead thedesign and implementation of quantitative data quality frameworksincluding statistical checks and anomaly detectionsystems.
• Utilizeadvanced statistical methods (e.g. linear and nonlinear modellingBayesian analysis) to evaluate data quality across large complexdatasets.
• Developand integrate AI / ML models for predictive data quality checks andto improve data accuracy over time. Improvement in datacollection
• Ensurecompliance with financial regulations and industry standardsrelated to data governance including managing data privacy andsecurityrisks.
• Mentorjunior quantitative analysts promoting best practices in dataquality management and statisticalanalysis.
• Communicatefindings data quality trends and proposed solutions to seniorleadership ensuring datadrivendecisionmaking.
• Lead thecreation and maintenance of automated test scripts to improve testefficiency.
• Ensurecontinuous integration of automated tests into the CI / CDpipeline.
• Identifygaps in testing coverage and proposesolutions.

Requirements

• StatisticalExpertise : Advanced knowledge of statistical methods includinglinear / nonlinear modelling hypothesis testing and Bayesiantechniques.
• AI / MLIntegration : Strong skills in applying AI / ML algorithms (e.g.neural networks random forest anomaly detection) for data qualitychecks and predictive analysis.

Experience with cloudbasedenvironments (AWS Azureetc.).

• QuantitativeFinance : Deep understanding of financial instruments market dataand the use of quantitative methods in portfolio management andriskanalysis.
• ProgrammingSkills : Proficiency in statistical programming languages (Python RSQL) and experience with tools like MATLAB SAS or similarplatforms.
• Automation : Experience in developing and implementing automated data validationprocesses including realtime monitoring and alertsystems.
• DataGovernance : Strong knowledge of data management principlesregulatory compliance and data governance practices particularly inthe context of financialservices.
• Leadership& Mentorship : Ability to mentor and guide junior team memberssharing expertise in statistical analysis AI / ML and data qualitybestpractices.
• ProblemSolving : Excellent analytical skills to identify root causes ofdata quality issues and implement longtermsolutions.
• Collaboration : Strong ability to work with crossfunctional teams including datascientists engineers and financial experts to enhance overall dataquality.

Mike

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