Data Architect – Senior

Role :
Data Architect – Senior

Client: Government of Alberta – Justice

Project: Justice Information Management System (JIMS 3.0)

Location: Primarily Remote – Canada;
Edmonton onsite meetings as required

Onsite Requirement: Approximately 15% of total hours

Hours: 36.25 hours/week

Contract: Approximately 1,805.25 hours, with potential extension up to 24 months

The Government of Alberta – Justice is seeking a Senior Data Architect to support the Justice Information Management System (JIMS 3.0) project.

JIMS 3.0 is a major data integration and modernization initiative designed to consolidate multiple existing court-data reporting marts into an integrated Enterprise Data Warehouse (EDW) and supporting data marts and reporting views.

The Senior Data Architect will be responsible for defining the data architecture, developing dimensional data models, profiling and analyzing source data, designing data mappings, supporting ETL development, and ensuring data quality and governance. The resource will work closely with technical teams, business stakeholders, and enterprise architecture teams to transition existing court-data environments toward the JIMS 3.0 target architecture.

The ideal candidate will have strong Kimball dimensional modeling, data warehouse, SQL, Azure/cloud, data architecture, and public-sector experience
.

Experience with
JOIN, JIMS, court data, and Justice environments is highly desirable.

• Define, document, and manage data architecture principles, strategies, standards, models, guidelines, and plans.
• Develop current-state and future-state data architecture and transition plans.
• Ensure data architecture aligns with Government of Alberta Enterprise Architecture (GAEA) and IMT strategies.
• Define enterprise data requirements and architectural standards.
• Provide data architecture guidance and consulting to project teams.
• Participate in architectural and solution design reviews.
• Identify opportunities to improve data reuse, sharing, governance, and standardization.
• Ensure data architecture reduces unnecessary data redundancy.
• Support the enterprise architecture team with data architecture initiatives.

• Apply Kimball dimensional modeling principles to design enterprise data marts.
• Develop conceptual, logical, and physical data models.
• Identify and define appropriate Facts, Dimensions, measures, attributes, keys, and relationships
  .
• Review and update existing data models.
• Develop data structures required for the JIMS 3.0 EDW.
• Define data warehouse and data-mart architecture patterns.
• Create detailed data mapping and transformation specifications.
• Ensure historical data is appropriately preserved and managed.

• Perform detailed profiling of source data and database tables.
• Analyze existing JIMS and related data marts.
• Identify data-quality issues, inconsistencies, redundancies, and gaps.
• Analyze business rules and relationships within court data.
• Map source data to target EDW structures.
• Validate data definitions and business rules with stakeholders.

• Design, develop, and test ETL/ELT processes
  .
• Support data extraction, transformation, staging, and loading.
• Develop source-to-target mappings.
• Validate transformed data against business requirements.
• Troubleshoot data integration and transformation issues.
• Support minor fixes and enhancements to existing data marts.

• Develop Power BI reports for testing and validation purposes.
• Use reporting outputs to validate Facts, Dimensions, measures, and business rules.
• Support interactive reporting requirements.
• Validate data quality and completeness through reporting.
• Collaborate with reporting and BI teams to ensure data structures support analytical requirements.

• Analyze and update existing JOIN (Justice Online Information Network) data models.
• Incorporate new Fact attributes and required data structures.
• Work with JIMS data and structures.
• Understand and document business rules associated with judicial processes
  .
• Support integration of court-related data into the enterprise data warehouse.