Knowledge Quality Consultant

Overview

As Knowledge Quality Lead, you will define and operate a multi-dimensional quality framework for enterprise knowledge graphs, ensuring completeness, correctness, provenance, and currency of data. You will drive governance, audits, and remediation at scale, collaborating with engineering, ontology, and AI teams to raise data quality across ecosystems. Your work supports trusted analytics and AI use cases by delivering observable quality improvements and governance-ready data. This role offers shaping enterprise data quality standards in a globally distributed organization.

Pay / Benefits

• remote or hybrid work options
• flexible work arrangements subject to client requirements
• global employer credentials
• opportunity to work on enterprise-scale data initiatives
• collaboration with cross-functional teams
• growth in AI/data governance domain

Responsibilities

• Define and implement a multi-dimensional quality framework with ongoing refinement of quality benchmarks
• Establish metrics for completeness, correctness (binding correctness), provenance, and currency
• Conduct periodic data quality audits using graph analytics and Cypher for validation
• Design dashboards and scorecards to communicate quality trends and risks to stakeholders
• Prioritize remediation backlog and enforce remediation SLAs; governance for ongoing QA
• Collaborate with data engineering, ontology, and AI teams to resolve issues and align with governance
• Promote best practices in data quality management and validation across the enterprise

Key requirements

• Data Quality Frameworks (profiling, validation, governance)
• Graph Analytics
• Cypher (querying and validation in graph environments)
• Audit Methodology (data audits, controls, compliance)

• Stakeholder management
• Cross-functional collaboration
• Communication and reporting
• Knowledge graphs / Neo4j (preferred)
• Data governance and metadata management
• Dashboarding tools (Power BI, Tableau)

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