Data Quality Engineer

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Overview

LABUR is partnering with a client for a Data Quality Engineer who engineers and operationalizes data quality across the enterprise data ecosystem, leading the design of automated testing frameworks, validation strategies, and monitoring capabilities. This role will collaborate closely with data engineers, business stakeholders, and governance teams to translate business and technical requirements into scalable quality controls while supporting the implementation of Informatica IDMC capabilities, including Data Quality and Cloud Data Governance & Catalog (CDGC).

Responsibilities

• Design, develop, and maintain scalable data quality and automated testing frameworks for data pipelines, transformations, data models, and published data products, covering completeness, accuracy, validity, consistency, uniqueness, timeliness, and reconciliation checks.
• Author and execute test plans, test cases, and automated validation routines; expand coverage through functional, regression, integration, reconciliation, and data performance testing strategies appropriate to enterprise analytical workloads.
• Embed automated data quality and regression testing into CI/CD pipelines, establishing quality gates that catch defects before deployment and validate data integrity post-release.
• Lead root-cause analysis of data quality defects, partnering with engineering and business teams to pinpoint source-data, transformation, modeling, and integration issues and drive timely remediation.
• Support the implementation and operationalization of Informatica CDGC, leveraging metadata, lineage, business rules, and governance capabilities to strengthen traceability, compliance, and audit readiness.
• Establish data quality KPIs, thresholds, monitoring, alerting, and exception-management processes for proactive detection of anomalies, errors, and unexpected changes in production data.
• Evaluate and incorporate AI-assisted capabilities into data quality practices — including test case generation, anomaly detection, data profiling, and root-cause analysis — while maintaining appropriate human oversight and governance controls.
• Collaborate across Data Services, Business Intelligence, Software Engineering, Platform Engineering, and Audit teams to integrate quality practices and advocate for data quality throughout the development lifecycle.
  
  

Qualifications

• 7 years of progressive experience in data engineering, data quality, software/data testing, or related data platform roles.
• Hands-on experience with enterprise data quality and governance technologies; Informatica IDMC Data Quality and Cloud Data Governance & Catalog (CDGC) experience strongly preferred.
• Strong proficiency in SQL and experience with Python for data validation, test automation, profiling, and quality engineering.
• Direct experience designing automated testing frameworks, developing test strategies, and integrating data quality validation into DevOps/CI/CD pipelines.
• Strong understanding of metadata management, lineage tracking, data profiling, cloud data architecture, and modern data platform concepts.
• Experience working in property & casualty insurance or other regulated industries with compliance requirements (e.g., SOX, audit readiness).
• Bachelor's degree in management information systems, computer science, engineering, or a related field (or equivalent experience); certifications in Informatica Data Quality, Data Governance, AWS, or test automation are a plus.
  
  

Compensation

$80-$85/hr - Dependent on fit and experience.