Data Architect/Modeller
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Summary
Senior Data Architect/Data Modeller contract (via Upstaff) for the Government of Ontario, based in Toronto: developing conceptual, logical, physical, semantic, canonical and enterprise data models, business glossaries and controlled vocabularies to enable data interoperability and governance, using tools like ERwin, PowerDesigner or Visio.
Position Overview
The Government of Ontario is seeking a Senior Data Architect / Data Modeller with extensive hands-on experience in conceptual, logical, physical and semantic data modelling. The successful candidate will develop enterprise, common, canonical and domain data models that enable interoperability, information exchange and data sharing across multiple business domains.
This role requires strong expertise in data architecture, semantic modelling, business vocabulary standardization, metadata management and enterprise data governance. The resource will work closely with business stakeholders, technical teams, enterprise architects and data governance professionals to establish consistent business definitions, data standards and reusable data models aligned with enterprise architecture requirements.
The ideal candidate will have demonstrated experience facilitating business and technical workshops, reconciling terminology across domains, developing business glossaries and reference data models, and translating business architecture requirements into practical data architecture deliverables.
Key Responsibilities
- Develop, maintain and implement conceptual, logical, physical, semantic and enterprise data models to support complex application development and enterprise information management requirements.
- Design and develop common data models (CDMs), canonical data models and domain data models that enable interoperability, information exchange and data sharing across multiple business domains.
- Establish common business definitions, controlled vocabularies, semantic models and canonical business definitions to support consistent interpretation and reuse of enterprise data.
- Define business entities, attributes, relationships, hierarchies, constraints and business rules across business and technical domains.
- Develop and maintain business glossaries, reference data models, semantic relationship models and standardized data definitions.
- Facilitate business and technical workshops to identify, define, validate and reconcile business terminology, business entities, relationships and canonical definitions across stakeholder groups.
- Apply domain-driven modelling and business capability analysis to develop common data models aligned with business requirements and enterprise architecture.
- Establish and enforce data modelling standards, naming conventions, normalization practices and metadata requirements.
- Design reference data and master data structures to support consistent information management and enterprise data governance.
- Define data architecture strategies, data flows, database locations, data distribution approaches and data access methods within complex and distributed environments.
- Support data interoperability, information exchange, data integration, migration and modernization initiatives.
- Develop architecture artefacts and checkpoint deliverables with traceability to business architecture requirements and enterprise architecture standards.
- Review conceptual, logical and physical data models for quality, consistency, completeness and adherence to established standards.
- Apply knowledge of metadata management, data lineage, data dictionaries, repository functions and information resource management practices.
- Evaluate data architecture and modelling solutions for scalability, performance, maintainability and alignment with enterprise data requirements.
- Support data prototyping, proof-of-concept activities and the development of recommendations for data interoperability and information exchange.
- Collaborate with enterprise architects, business analysts, developers, data governance teams and other stakeholders to ensure alignment between business needs and technical implementation.
- Contribute to architecture governance, design reviews and the development of enterprise architecture deliverables.
- Communicate data architecture concepts, modelling decisions, standards and recommendations clearly to technical and non-technical audiences.
- Monitor emerging information technology trends and apply relevant data architecture methodologies, tools and best practices.
Mandatory Qualifications and Experience
Candidates must demonstrate the following qualifications and experience:
- Hands-on data modelling: Demonstrated experience developing conceptual, logical and physical data models, with practical experience in semantic data modelling.
- Enterprise and common data modelling: Extensive experience developing enterprise, common, canonical and domain data models that support interoperability, information exchange and data sharing across multiple business domains.
- Data architecture expertise: Deep knowledge of data architecture principles, methodologies, standards and industry best practices.
- Business definitions and semantic models: Demonstrated experience establishing common business definitions, controlled vocabularies, semantic models and common data models to support interoperability, information sharing and enterprise data governance across multiple business domains.
- Workshop facilitation: Experience facilitating business and technical workshops to define and reconcile business terminology, business entities, relationships and canonical definitions.
- Business glossaries and reference models: Experience developing business glossaries, reference data models and semantic relationship models.
- Data modelling tools: Experience using data modelling and CASE tools such as ERwin, PowerDesigner, Visio or equivalent tools.
- Data standards and metadata: Experience establishing modelling standards, naming conventions and metadata requirements.
- Business entities and relationships: Experience defining entities, relationships, hierarchies, attributes and business rules.
- Information exchange and integration: Experience supporting interoperability, information exchange and data integration initiatives.
- Architecture artefacts: Experience developing architecture artefacts and checkpoint deliverables with traceability to business architecture requirements.
- Data governance: Knowledge of metadata management, data lineage and data governance principles.
- Data modernization: Experience supporting data migration, integration and modernization initiatives.
- Analytical and communication skills: Strong analytical, problem-solving and communication skills, including the ability to collaborate effectively with business and technical stakeholders.
Requirements
Expected Deliverables
The successful candidate will be responsible for producing and supporting the following deliverables:
- Common Data Model (CDM)
- Canonical Data Model
- Conceptual Data Models
- Logical Data Models
- Physical Data Models
- Semantic Data Models
- Enterprise and Domain Data Models
- Business Glossary
- Controlled Vocabulary
- Canonical Business Definitions
- Reference Data Models
- Semantic Relationship Models
- Data Standards and Naming Conventions
- Metadata requirements and related modelling artefacts
- Architecture artefacts supporting architecture governance and review processes
- Data interoperability and information exchange recommendations
- Data prototypes and proof-of-concept deliverables
- Documentation demonstrating traceability to business architecture requirements
Desirable Qualifications and Experience
The following experience will be considered an asset:
- Experience developing common data models, business vocabularies and semantic frameworks for regulatory, permitting, licensing, compliance or public-sector programs involving multiple business domains and stakeholder groups.
- Experience with semantic modelling, ontology development or knowledge graph concepts.
- Knowledge of RDF, OWL, graph databases and semantic technologies.
- Experience with Databricks, Neo4j, Denodo or equivalent data platforms.
- Experience with metadata repositories and data governance solutions.
- Knowledge of Information Management principles, concepts, policies and practices.
- Knowledge of AODA and related accessibility standards.
- Experience supporting permitting, regulatory, licensing or other public-sector business domains.
- Experience with middleware, gateways and automated data distribution mechanisms.
- Knowledge of dimensional and relational data models, database performance considerations and data normalization.
- Experience with Ontario Government Enterprise Architecture processes and practices.
- Knowledge of object-oriented analysis and design techniques.
- Experience with information resource management tools and techniques.
- Experience working in complex, distributed systems environments involving multiple platforms, operating systems, database technologies, programming languages and communication protocols.
- Experience using structured methodologies for application design, development and implementation.
General Competencies
- Excellent analytical, problem-solving and decision-making skills.
- Strong verbal and written communication skills.
- Effective stakeholder engagement, facilitation, interpersonal and negotiation skills.
- Ability to translate complex business requirements into clear, standardized and reusable data models.
- Ability to work collaboratively across business and technical teams.
- Strong organizational skills and a demonstrated track record of meeting deadlines.
- Awareness of emerging information technology trends, data architecture practices and enterprise information management standards.
Important Submission Considerations
This is a senior-level, hands-on data architecture and modelling assignment. Candidates should clearly demonstrate their practical experience developing conceptual, logical, physical and semantic data models, together with enterprise, common, canonical and domain data models.
Particular emphasis will be placed on experience standardizing business terminology across multiple domains, developing controlled vocabularies and canonical business definitions, facilitating business and technical workshops, and delivering business glossaries, reference data models and semantic relationship models.