Senior Data Architect to support data strategy and governance improvements for data-driven Informatica solutions (RFS1016656)

Our large, enterprise client is seeking a Senior Data Architect to support data strategy and governance improvements for data-driven Informatica solutions. The Data Architect is responsible to perform Data analysis, data strategies and governance, prescribed methods, industry best practices, information architecture, data schema's, detailed data specifications, integration patterns, and similar.

This is an initial approximate 2-year contract with a possibility of extension. The ideal candidate will be based in Regina, SK, and agreeable to working full-time in office.

Must-Haves:

• 5+ years' experience with data governance, strategies, and related information architecture principles
• Experience building dashboards, reports, and data driven solutions
• Experience developing data strategies and data governance model, including with diagrams and logical flows.
• University degree in Administration, Computer Science, Information Architecture, Data Analytics, Software Engineering, or related study

Nice-to-Haves:

• Certification and experience with The Open Group Architectural Framework (TOGAF)
• Experience using Informatica Data Quality, Enterprise Service Bus (ESB), SparxEA or equivalent data governance technology

Deliverables:

• Promote and educate data governance principles and practices.
• Facilitate working sessions with business and technical audiences around data governance.
• Develop data and data governance standards in collaboration with business subject matter experts.
• Document data lineage, integrations & transformations across the enterprise.
• Map data transformations to business process and practices.
• Facilitate identification, documentation & socialization on systems of record.
• Create and maintain Data Architecture documentation on projects.
• Lead data scorecard development.
• Identify data roles and responsibilities across business areas and data categories.
• Document data quality issues and classification of issues into categories.
• Create strategies and process to track, improve data.
• Profile data based on risk and strategic priorities.
• Contribution to concept, methodology, component definition, improvement
• Contribution and guidance on industry directions and best practices
• Deliver solutions using agile sprint methodology.