Data Quality Engineer

The Data Quality Engineer owns the implementation and continuous improvement of data quality across critical business domains. The role ensures data is accurate, consistent, and usable across enterprise systems including ERP, CRM, analytics platforms, and customer-facing applications, while reducing operational inefficiencies and improving trust in data.

Key Responsibilities

• Define, implement, and maintain data quality rules aligned to business processes and use cases.
• Monitor data quality across core ISO-8000 data quality standards (i.e. completeness, accuracy, consistency, validity, uniqueness, referential integrity, and timeliness).
• Design and implement data quality monitoring and alerting to proactively identify issues as they arise, with a focus on reducing recurring data issues, manual corrections, and downstream operational impacts.
• Perform root cause analysis on data issues across source systems, pipelines, and downstream applications.
• Own cross-system data quality validation, ensuring data integrity is enforced at ingestion, transformation, and load stages
• Partner with business stakeholders and technical teams to establish and steward accountability for data ownership, business definitions, and quality expectations across enterprise systems.
• Design and support remediation workflows to ensure timely resolution of data quality issues with clear ownership and resolution SLAs.
• Support implementation of data classification standards (e.g., PII, sensitive data) in alignment with GDPR, CCPA, applicable regulatory requirements and AI initiatives.
• Leverage Microsoft Purview to improve visibility into data lineage, definitions, ownership, and classification.
• Define and track data quality KPIs; report regularly on quality trends, issue resolution rates, and business impact to leadership and governance stakeholders