Data Quality Architect

Job Title: Data Quality Architect

Team: Data Governance

Location: Cincinnati, OH-Onsite

Role Summary

The Data Quality Architect will lead the planning and execution of data quality management for critical datasets, including regulatory reporting. This role will design and implement data quality practices across multiple channels to ensure accuracy, consistency, and compliance. The architect will collaborate with data producers, consumers, and governance teams, and may be deployed directly to agile squads for focused delivery.

Primary Responsibilities

• Leadership in Data Quality Management:
• Own the strategy, planning, and execution of data quality initiatives for critical datasets.
• Drive adoption of enterprise standards and ensure alignment with governance objectives.
• Architect and Advise:
• Define and implement data quality frameworks, standards, and controls aligned with:
• Critical Data Standard – Apply control objectives for critical data assets.
• Data Product Standard – Embed quality requirements into data products.
• Data Quality Management Guidance – Implement Ataccama-based rules, anomaly detection, and operational checks.
• Data Quality Management:
• Apply data quality rules and anomaly detection using platforms such as Ataccama.
• Design operational checks and reconciliation processes for in-line data validation.
• Critical Data Oversight:
• Focus on high-risk and regulatory reporting datasets, ensuring compliance with internal and external standards.
• Collaboration:
• Work closely with data consumers and product teams to embed quality controls into data pipelines and products.
• Provide guidance to squads on data profiling, grading, and remediation strategies.
• Continuous Improvement:
• Monitor and report on data quality metrics, root cause analysis, and remediation plans.
• Champion automation and scaling of data quality capabilities across the enterprise.

Required Skills & Experience

• Strong knowledge of data quality management principles and tools (Ataccama preferred).
• Experience with data architecture, governance frameworks (e.g., DCAM), and regulatory compliance.
• Ability to design and implement data profiling, anomaly detection, and reconciliation processes.
• Excellent communication skills for stakeholder engagement across technical and business teams.
• Familiarity with agile delivery and ability to work within squads.

Preferred Qualifications

• Banking or financial services experience with regulatory reporting data sets.
• Hands-on experience with data cataloging, lineage, and critical data element management.