Job Description
- Provide professional information architecture expertise and undertake comprehensive architecture needs assessments and complex reviews in support of enterprise data and information management needs, including data mesh operating models, data product standards, and interoperability frameworks.
- Participate in enterprise-wide and cross-jurisdictional architecture projects with information and data-sharing components, ensuring alignment with federated governance models, master/reference data strategies, and common information exchange standards.
Requirement/Must Have
- Define, identify, and describe enterprise information architectural requirements with clients, including data product specifications, metadata standards, and interoperability needs, and obtain management approval.
- Develop and obtain approval for detailed plans and resource estimates for large-scale and complex information architecture projects and/or components with information architecture elements, including data mesh governance, master data management, and information exchange standards.
- Knowledge and understanding of Information Management principles, concepts, policies, and practices, including federated governance and data mesh operating models.
- Knowledge of metadata management, lineage standards, and FAIR principles for data discoverability and reuse.
- Ability to write and draft a wide range of documents such as briefs and memos suitable for technical and non-technical audiences.
Should Have
- Experience with Computer Aided Software Engineering (CASE) tools.
Skills
Information And Data Architecture (50%):
- Ability to complete complex information architecture reviews and assessments to support new and evolving enterprise priorities and initiatives.
- Research, develop, implement, and maintain information architectural policies, standards, and playbooks.
- Provide information architecture interpretation and expertise on data mesh principles, interoperability standards, and master/reference data governance.
- Lead or participate in sensitive information architecture investigations, including impact analysis for schema changes and cross-domain interoperability issues.
- Develop information architecture specifications for RFPs, embedding interoperability, open standards, and accessibility requirements.
- Create enterprise-level information architecture artefacts such as logical and information data models, semantic models, controlled vocabularies, canonical entity definitions, and interoperability profiles.
Enterprise Data Management / Enterprise Information Management (20%):
- Knowledge of metadata management, lineage standards, FAIR principles, and federated governance.
- Ensure integration with corporate and client policies and incorporation of best practices in federated data governance, privacy-by-design, and accessibility.
- Develop checkpoint deliverables and governance compliance artefacts.
- Experience developing canonical data models to support interoperability within federated governance environments.
Communication Skills (15%):
- Strong writing and drafting skills for diverse audiences.
- Strong presentation skills, including preparation of visuals and slide decks for executives and staff.
- Ability to collaborate effectively with analysts, architects, administrators, and project stakeholders.
- Strong relationship management between clients and IT organizations.
Problem Solving And Analysis (15%):
- Support development of consumption-oriented data sets and tools for operational and analytical needs.
- Conduct research and analysis to support policy deliverables and tools enabling Enterprise Information Management programs.
Qualification And Education
- High school diploma or equivalent required.
- Preferred: Post-secondary education in Information Management, Computer Science, or a related field.
Desirable Skills
- Experience with Computer Aided Software Engineering (CASE) tools.
- Experience defining and implementing data product standards, data contract specifications, and reference data services.
- Familiarity with semantic modeling, taxonomies, controlled vocabularies, and canonical definitions.
- Understanding of privacy and security frameworks (FIPPA/MFIPPA), classification, and de-identification methods.
- Knowledge of information exchange standards (e.g., NIEM, OpenAPI, AsyncAPI, JSON Schema).
- Awareness of data quality frameworks and governance automation (policy-as-code).