Senior Data Architect

The Senior Data Architect/Modeller is responsible for developing and implementing comprehensive data architectures and models across complex, distributed environments. This role ensures alignment with enterprise strategies by creating and maintaining conceptual, logical, physical, canonical, and semantic data models that support interoperability, information exchange, and data governance across multiple business domains. The position requires strong analytical skills, expertise in data modelling tools, and experience facilitating cross-functional workshops to establish standardized business vocabularies and data definitions. Responsibilities:

• Develop and implement data architecture for application development in complex distributed environments.
• Create and maintain conceptual, logical, physical, canonical, and semantic data models supporting multiple business domains.
• Define data flow, database locations, and data access methods aligned with enterprise strategies.
• Establish and enforce data modelling standards, naming conventions, and metadata requirements.
• Develop and maintain business glossaries, controlled vocabularies, canonical business definitions, and reference data models.
• Facilitate business and technical workshops to define and reconcile business terminology and data relationships.
• Support interoperability, data integration, data migration, and modernization initiatives.
• Produce architecture artefacts and deliverables aligned with business architecture requirements and governance processes.
• Monitor emerging information and IT trends relevant to data architecture and modelling.
• Provide recommendations for data interoperability and information exchange improvements.

• Extensive hands-on experience with conceptual, logical, semantic, and physical data modelling.
• Proficiency in data modelling tools such as ERwin, PowerDesigner, Visio, or equivalent CASE tools.
• Deep knowledge of data architecture principles, methodologies, standards, and best practices.
• Experience developing enterprise, common, canonical, and domain data models to support interoperability and data sharing.
• Ability to establish common business definitions, controlled vocabularies, and semantic models.
• Strong facilitation skills for conducting business and technical workshops.
• Knowledge of metadata management, data lineage, and data governance principles.
• Experience supporting data migration, integration, and modernization projects.
• Excellent analytical, problem-solving, communication, and interpersonal skills.

• Experience with middleware, gateways, and automated data distribution mechanisms.
• Knowledge of object-oriented analysis and design techniques.
• Familiarity with Ontario Government Enterprise Architecture processes and practices.
• Experience creating detailed data standards for system integration.
• Understanding of dimensional and relational data models.
• Experience with semantic modelling, ontology development, or knowledge graph concepts.
• Knowledge of RDF, OWL, graph databases, or semantic technologies.
• Experience with data platforms such as Databricks, Neo4j, or Denodo.
• Familiarity with metadata repositories and governance solutions.
• Understanding of Information Management principles, policies, and AODA standards.
• Experience supporting regulatory, permitting, licensing, compliance, or public sector business domains.

• Data Modelling Expertise (Conceptual, Logical, Physical) - 30 Points
• Development of Enterprise and Canonical Data Models - 25 Points
• Facilitation of Business and Technical Workshops - 15 Points
• Knowledge of Data Governance and Metadata Management - 10 Points
• Experience with Data Architecture Tools and Methodologies - 10 Points
• Analytical and Communication Skills - 10 Points

• Common Data Model (CDM) and Canonical Data Model
• Conceptual, Logical, and Semantic Data Models
• Business Glossary and Controlled Vocabulary
• Canonical Business Definitions and Reference Data Models
• Semantic Relationship Models
• Data Standards and Naming Conventions
• Architecture Artefacts for Governance and Review Processes
• Data Interoperability and Information Exchange Recommendations
• Data Prototyping and Proof-of-Concept Activities

• Hands-on experience with conceptual, semantic, logical, and physical data modelling.
• Extensive experience developing enterprise, common, canonical, and domain data models supporting interoperability and data sharing.
• Deep knowledge of data architecture principles, methodologies, standards, and best practices.
• Proven ability to establish common business definitions, controlled vocabularies, and semantic models.
• Experience facilitating workshops to define and reconcile business terminology, entities, and canonical definitions.
• Strong analytical, problem-solving, and communication skills.

Preferred