Senior Associate - Data Quality Analyst

New York Life•New York, NY

12d•$100,000 - $143,000•Hybrid

About The Position

We are seeking a strong Data Quality Analyst with a robust data analysis skillset to support New York Life’s enterprise-wide data management and governance initiatives. This individual contributor role partners closely with AI & Data product managers, business subject matter experts (SMEs), and technology teams to define data quality requirements, implement monitoring and alerting, and support issue management for critical data elements (CDEs). This role also supports broader governance capabilities, including Data Strategy, Data Catalog & Curation, and Data Protection, enabling both client-based and agency-led initiatives while delivering governance solutions to a wide range of internal stakeholders. What You’ll Do: As a Data Quality Analyst, you will play a critical role in ensuring the reliability, accuracy, and consistency of enterprise data.

Requirements

Bachelor’s degree in Information Technology, Computer Science, Mathematics, Engineering, or a related field
3–5 years of experience in data quality, data governance, or data engineering
Proficiency in SQL and related programming languages
Familiarity with ELT tools and concepts (e.g., dbt)
Knowledge of data governance, master data management (MDM), reference data management (RDM), and metadata management
Strong communication and collaboration skills
Strong documentation and reporting skills, with the ability to communicate findings and improvement opportunities

Responsibilities

Develop and Implement Data Quality Frameworks
Design, build, and maintain automated data validation checks and anomaly detection across datasets from multiple systems and sources.
Conduct Data Quality Assessments & Root Cause Analysis
Proactively identify data issues, perform root cause analysis, and support remediation through the enterprise issues management process.
Collaborate with Stakeholders
Partner with business, IT, and analytics teams to understand data quality requirements for critical data elements (CDEs) and support data owners with insights to prioritize issue resolution.
Enhance Data Pipelines & ELT Processes
Work closely with data engineers to ensure ingestion and transformation processes meet data integrity, completeness, and timeliness standards. Support testing and validation of pipeline changes.