Job Title

Project Overview Project Name: OPGT Public Trustee Information System Replacement Scope: GoA's Office of the Public Guardian and Trustee (OPGT) provides services for personal/financial matters to vulnerable Albertans. Financial services use comprehensive case management and financial systems for trust administration. This project replaces their legacy system with Microsoft Dynamics' Customer Relationship Management and Financial components. System development is underway by an external vendor with golive in late 2026. Agile sprint development is in place with a waterfall timeline for full release of the solution. The delivery team is supported by a GoA team (Manager, Product Owner, Change Manager/Trainer, Data Migration Team, Testers), vendor development team, and Technology and Innovation's (T&I) technical/privacy/security teams, and business stakeholders/SMEs. OPGT: https://www.alberta.ca/office-public-guardian-trustee.aspx Role Summary The Data Architect is critical in defining, executing and managing data architecture domain to ensure project, security, technical and strategic objectives are met. The role provides leadership and expertise across architecture design, governance, security, and modernizationensuring alignment with GoA standards and business needs. Working closely with stakeholders, the role leads design/development of overarching data requirements and establishes principles, strategies, architectures, methods, models, standards and plans needed to provision data for the solution. They will establish a secure, high performing, analytics ready data architecture that supports operations, enterprise reporting and advanced analytics. Responsibilities Architecture Leadership - Define/document data architecture (data requirements, strategies/plans, architecture, design principles, models, integration diagrams etc.) - Lead solution architecture and design on cloud and key data platforms. Ensure alignment with business requirements. - Lead design and governance of schemas, tables, relationships, security roles and data access patterns. - Promote data models and practices to reduce redundancy. - Guide platform/infrastructure teams to configure data platform services to meet solution requirements. - Participate in planning on implementation strategy, technology stack, design patterns and process. - Advise on configuration vs customization to support long term sustainability. - Review/approve vendor delivered data designs, strategies and implementations. - Advise and coach teams throughout project. Provide knowledge transfer. Enterprise Data Architecture - Define endtoend data architecture, including all integrated applications and systems; develop conceptual, logical and data models aligned with platform standards, enterprise data policies, including Dataverse data modeling. - Ensure architectural alignment across system modules, integrated applications, Power Platform components, Azure and downstream reporting environments. - Establish data architecture principles and standards consistent with GoA architecture frameworks. - Architect integrations between solution and external systems, including legacy platforms, document repositories, etc. - Ensure data exchanges meet security, privacy and auditability standards. - Work with Microsoft Dynamics to design how data is organized, stored, integrated and managed across Dynamics 365 ecosystem and broader Microsoft cloud environment (Power Platform, Azure, Fabric). - Work with Microsoft Dynamics' Finance & Operations for managing financial data. Data Migration - Serve as GoA lead in data mapping from legacy platform to the new application, ensuring accurate lineage, transformations and alignment with new data models. - Collaborate with vendor to validate mapping logic, support build activities, and ensure mappings are technically feasible. - Work with business areas to define/confirm data rules, resolve data gaps, and ensure mappings support functional, operational, and reporting needs. - Lead data migration strategy. Define extraction, transformation, cleansing, and validation approaches aligned with business rules. Ensure data integrity, traceability, and reconciliation throughout migration activities. - Support parallelrun and cutover strategies to minimize business disruption. Data Lakehouse Architecture & Design - Define data warehouse/lakehouse approach and architecture and related requirements. - Define storage, archival and retrieval approach for legacy data and target data structures and storage solutions for new system data to ensure performance and long term maintainability. - Use Microsoft tools to create a modern data warehouse/lakehouse (e.g. Azure Services Azure Data Lake Storage, Azure Synapse Analytics and Azure Databricks for big data processing, analytics, data warehousing). - Design data mesh/lakehouse architectures using Microsoft Azure technology stack to unify data management and analytics. Data Quality & Readiness - Define data quality standards, validation rules and acceptance criteria for migrated and operational data. - Support business validation activities, including sampling, reconciliation and exception management. - Ensure data readiness across project stages (e.g. user acceptance testing, training, golive). - Identify and mitigate datarelated risks early. Data Governance & Compliance - Ensure compliance with GoA policies privacy, records management, data retention, access control, etc. - Define and enforce data classification, retention schedules, and information lifecycle management within platform and integrated platforms. - Collaborate with security, privacy, records management teams to implement data governance practices/controls. Support audits, compliance reviews, architectural assurance processes. Reporting - Ensure new solution and data architecture enable effective reporting/analytics, including in solution dashboards and Power BI reports. - Define data flows into reporting platforms and downstream analytics environments. - Ensure consistency between operational and analytical data models. - Ensure architecture security, enforcing data/reports are only accessible to certain individuals/groups. - Implement anonymization, restricting access to sensitive data from certain individuals/groups. Delivery Oversight - Oversight across Agile delivery cycles, ensuring data considerations are embedded early in design and backlog refinement. - Participate in sprint planning, backlog grooming and design reviews from an architecture perspective. - Identify dependencies, risks, constraints impacting timelines. Support realistic sequencing/release planning for datarelated work. - Develop project plans/schedules and estimates for data activities. Develop task lists and resource assignments to ensure completion of data activities. Vendor & Stakeholder Collaboration - Collaborate/consult effectively with project stakeholders. Review vendor deliverables for compliance/quality. - Translate technical data concepts, risks, options and recommendations into clear, actionable guidance for business stakeholders. Provide strategic guidance. Support executive decisionmaking. - Document technical recommendations. #J-18808-Ljbffr