Data Architect - Senior at Procom
Edmonton, AB, Canada -
Full Time


Start Date

Immediate

Expiry Date

26 Nov, 25

Salary

0.0

Posted On

27 Aug, 25

Experience

0 year(s) or above

Remote Job

Yes

Telecommute

Yes

Sponsor Visa

No

Skills

Agile, Platform Integration, Data Governance, Metadata

Industry

Information Technology/IT

Description

DATA ARCHITECT - SENIOR:

On behalf of our Government client, Procom is searching for a Data Architect - Senior for a long-term role. This position is a hybrid position with occasional days onsite at our client’s Edmonton office.

DATA ARCHITECT - SENIOR - JOB DESCRIPTION:

The project involves supporting the design, development, and implementation of cloud-based semantic architectures, services, and tools for the Government. The aim is to leverage data assets in alignment with the Data Strategy, facilitating cross-ministry integration and engagement with stakeholders.

DATA ARCHITECT - SENIOR - MANDATORY SKILLS:

  • Experience in semantic architecture design
  • Proficiency in cloud platform integration
  • Knowledge of data governance, metadata, and ontology management
  • Experience with AI infrastructure development
  • Strong stakeholder engagement skills
  • Ability to apply Agile and DevOps practices
  • Excellent communication and problem-solving skills

DATA ARCHITECT - SENIOR – NICE-TO-HAVE SKILLS:

  • Experience with generative AI tools
  • Knowledge of conversational user interfaces
  • Familiarity with Alberta’s data governance policies
  • Previous experience in a government setting
  • Understanding of advanced analytics-driven services
Responsibilities
  • Lead the design and implementation of semantic data models for AI applications and conversational interfaces.
  • Develop and manage ontologies, taxonomies, and metadata standards.
  • Document architecture decisions, standards, and best practices.
  • Architect and maintain scalable cloud-based infrastructure for semantic data integration.
  • Collaborate with multi-disciplinary teams to ensure interoperability.
  • Integrate AI tools with enterprise data systems for intelligent capabilities.
  • Support the development of AI-enabled data products and interfaces.
  • Ensure data privacy, security, and ethical AI practices in designs.
  • Provide technical leadership and mentorship to team members.
  • Monitor emerging technologies in semantic knowledge and AI.
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