Data Architect

Position Title: Data Architect

Location: Columbus OH (5 days onsite)

Duration: 6 Months (Contract to hire)

Looking for Information data architect

someone who have done major data analysis - not small scope

Job Description:

• Information Architect
• Expert in data architecture disciplines
• Expert in architecture and design across all systems of the LOB.

Role Summary:

• The Information Architect is responsible for designing and governing the structure semantics and organization of information across the enterprise.
• This includes developing taxonomies ontologies metadata schemas and navigation structures to ensure information is findable usable and consistent.
• The Information Architect works closely with data architects governance teams and business stakeholders to optimize information discoverability and clarity.

Key Responsibilities:

• Develop and maintain enterprise taxonomies ontologies controlled vocabularies and metadata schemas.
• Define and document canonical information models naming conventions and master data definitions.
• Design information navigation structures for portals catalogs and user interfaces.
• Partner with data governance to maintain data dictionaries lineage and stewardship policies.
• Collaborate with data architects and engineers to ensure information structures align with data platforms and integration patterns.
• Improve information discoverability usability and consistency across systems.
• Support data catalog glossary and metadata management initiatives.
• Provide guidance on information architecture best practices and standards.

Required Skills and Qualifications:

• Bachelors or Masters degree in Information Science Library Science Computer Science or related field.
• Experience in information architecture taxonomy/ontology design metadata management and knowledge organization.
• Familiarity with information cataloging tools (e.g. Collibra Alation) taxonomy/ontology editors and knowledge graph platforms.
• Strong understanding of data governance stewardship and master data management principles.
• Excellent analytical communication and stakeholder engagement skills.

Success Metrics:

• Consistent clear and discoverable information structures.
• Improved user experience and information findability.
• Effective collaboration with data and governance teams.
• Adoption of information architecture standards and best practices.