Senior Data Quality Engineer

We are seeking a technically strong Senior Data Quality & Governance Engineer to lead data quality automation and structural optimization efforts. This role is 60–70% Data Quality Engineering and 30–40% Data Stewardship, focused on redesigning data foundations to improve performance, scalability, and AI readiness.

• Conduct deep data audits and implement automated validation frameworks.
• Identify root causes of recurring data issues and implement structural fixes.
• Rearchitect and optimize data models, schemas, and relational structures.
• Implement SQL constraints, triggers, indexing, and performance tuning.
• Define and enforce data quality standards and governance policies.
• Utilize cataloging tools such as Collibra or Alation.
• Build dashboards and quality metrics using Microsoft Power BI or Tableau.
• Apply automated validation tools like Great Expectations or Soda.

• 5–7 years in Data Quality, Data Governance, or Data Stewardship roles.
• Proven experience redesigning or optimizing data structures.
• Proficiency in Python, R, or SAS for statistical data validation.
• Experience aligning data practices with compliance standards (e.g., HIPAA, NIST Cybersecurity Framework).
• Strong documentation and cross-functional communication skills.

This role is ideal for someone who can go beyond data cleanup and fundamentally improve how data is structured, validated, and governed to support scalable systems and AI initiatives.