Role
Metadata (Stewardship) Quality Consultant
Experience Guide
Senior: 5-9 years
Primary Skill Area
Metadata Management, Data Quality, Catalog Lineage
The opportunity
Drive trusted, discoverable, and usable data through data quality management, metadata management, business glossary, technical metadata, lineage, cataloging, stewardship, discovery, classification, and data asset certification practices.
Your key responsibilities
- Develop data quality management frameworks, rules, scorecards, and monitoring mechanisms.
- Perform data profiling, quality assessment, issue analysis, and remediation planning.
- Design and operationalize data catalog management, metadata standards, and business glossary practices.
- Manage technical metadata, lineage, data inventory, and data asset certification processes.
- Drive data discovery, data classification, and sensitive data inventory initiatives.
- Implement stewardship workflows, ownership models, and governance-enabled catalog processes.
- Support data marketplace enablement and self-service data discovery use cases.
- Support reference data management and master data management initiatives where applicable.
Skills and attributes for success
- Data Quality Management
- Data Quality Rules
- Profiling Monitoring
- Data Catalog Management
- Metadata Management
- Business Glossary
- Technical Metadata
- Data Lineage
- Data Discovery
- Data Classification
- Data Stewardship
- Data Inventory
- Data Asset Certification
- Data Marketplace
- Reference Data Management
- Master Data Management
To qualify for the role, you must have
- Relevant experience guide: Senior: 5-9 years.
Ideally, you'll also have
- Collibra
- Atlan
- Microsoft Purview
- Alation
- Informatica
- BigID
- Data quality and profiling tools
What we look for
- A governance skilled who can define practical operating models, drive adoption across business and technology teams, and translate governance controls into measurable delivery outcomes.
📌 EY-GDS Consulting-AI And DATA-Metadata-Senior (Hyderabad)
🏢 EY
📍 Hyderabad