Data Librarian / Metadata

Data Librarian/ Metadata Curator/ Taxonomist/ Information Architect/ Knowledge Manager/ Metadata Specialist Top Skill Areas for a Data Librarian Analytics Enablement Non-Academic Non-Academic looks to be more niche User-Centric Data Cataloging & Curation
Expertise with enterprise data catalogs (e.g., Collibra

Key Responsibilities:
Develop and maintain metadata catalogs and data dictionaries.
Support enterprise data governance efforts by documenting data definitions, lineage, and classification.
Collaborate with data stewards to ensure data standards are applied consistently.
Promote data literacy by supporting users in locating and understanding data assets.
Maintain tools and platforms for metadata and data cataloging (e.g., Collibra).
Conduct data inventory and gap analyses.
Monitor and support data lifecycle management processes.

Qualifications:
Bachelor s degree in Library Science, Information Science, Data Management, or related field (Master s preferred).
2 5 years of experience in data management, digital librarianship, or metadata management.
Familiarity with data cataloging tools and metadata standards (DCMI, ISO 11179, etc.).
Strong understanding of data governance, data quality, and compliance principles.
Excellent communication, documentation, and organizational skills.


Additional Information:
Data Librarian/ Metadata Curator/ Taxonomist/ Information Architect/ Knowledge Manager/ Metadata Specialist Top Skill Areas for a Data Librarian Analytics Enablement Non-Academic Non-Academic looks to be more niche User-Centric Data Cataloging & Curation
Expertise with enterprise data catalogs (e.g., Collibra)
Business-friendly documentation, asset tagging and certification
Strong Data Literacy & Enablement Mindset
Developing training materials and self-service guides
Facilitating onboarding to new datasets or tools
Hosting data walk-throughs or office hours
Understanding business processes
Translating technical metadata into business-friendly language
Supporting data democratization and user adoption
Communication Between Data Builders and Consumers
Acting as a translator between engineers and analysts
Gathering, translating, and documenting business and technical user requirements
Shaping naming conventions, glossary terms, and metric definitions
Stakeholder communication and collaboration across teams
BI Tool, Data Warehouse: Awareness & Integration
Familiarity with metadata and catalog integration (e.g., Power BI, Tableau)
Supporting lineage and asset descriptions
Basic familiarity with data platforms and tools (e.g., SQL, Azure, BI tools)
Understanding data models, pipelines, APIs, and architecture
Search Optimization & Findability
Creating and enforcing metadata standards for searchability
Ensuring consistent tagging, descriptions, and glossary terms
Creating and applying taxonomies, data models and tagging structures
Knowledge of data lineage, classifications, and business glossary management
Basic understanding of how search engines work; ability to configure metadata standards and field types to optimize search
Soft Skills that Drive Adoption
Empathy for users and understanding their challenges
Advocacy and influence to promote good documentation practices
Curiosity to explore dataset usage and issues
Change management and adaptability to evolving environments