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., * 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

Do you have experience in Stakeholder management?, Do you have a Bachelor’s degree?, * Bachelor’s Degree in Information Technology, Computer Science, Data Analytics, or a related field.

• Minimum of 3-5 years of experience in data quality, data engineering, data governance, or analytics roles.
• Strong proficiency in SQL for data analysis and validation.
• Experience working with data pipelines and transformation tools (Azure Data Factory preferred).
• Strong analytical and problem-solving skills, with the ability to diagnose data issues across systems.
• Strong communication skills, with the ability to work effectively with both technical and non-technical stakeholders.
• Ability to translate business needs into practical data quality solutions.
• Ability to operate independently with limited day-to-day supervision in a distributed team environment.
• Solid understanding of relational data modeling concepts, including entity relationships, normalization, and schema design across systems., * Experience working in commercial, distribution, and/or light manufacturing environments.
• Experience with data governance and metadata management tools (e.g., Microsoft Purview, Collibra, Alation, Informatica)
• Familiarity with master data management concepts (Customer and Product domains).
• Experience implementing data quality frameworks or working with standards such as DAMA-DMBOK or ISO-8000.
• Exposure to CRM (Salesforce, HubSpot) and/or ERP (Epicor).
• Experience supporting analytics platforms such as Power BI.

Key Competencies

• Data-driven problem solving in an enterprise environment.
• Cross-functional collaboration.
• Stakeholder engagement and influence.
• Process improvement and operational efficiency.