The Data and Information Architect is a senior technical role responsible for the design, governance, and delivery of corporate certified datasets within the corporate data platform This role combines deep data modelling expertise with strong delivery ownership, ensuring that complex datasets, including but not limited to project cost, timesheets, accounts payable, and financial summaries, are accurate, performant, and usable for business reporting and analytics The Data and Information Architect serves as the primary point of accountability for data architecture decisions, dataset standards, and cross-functional data enablement across the organization This position sits at the intersection of technical architecture, data delivery, and business stakeholder enablement, and requires both a strong technical foundation and excellent collaboration skills Data Architecture & Modelling: Design, document, and maintain enterprise data models including star schema, fact/dimension structures, and normalized dataset architectures Lead transformation from denormalized to normalized/star schema designs to improve data platform performance and end-user usability Define and maintain metadata, column naming conventions, mapping documents, and dataset structures for Orb datasets (e.G., Project Cost Detail, Time Sheet Posted Detail, Project Financial Summary By Period, Project Non Labour Cost Detail) Establish data filtering logic, global rules, and architectural standards to control dataset scope and platform performance Author and maintain enterprise data governance documents including Database Naming Conventions and Objects Naming Conventions (maintained since 2020, updated through 2025) Data Product Ownership Curated Datasets: Own and drive the delivery of corporate datasets Prioritize and sequence dataset deployments across pre-production, UAT, and production environments Ensure source to platform data accuracy and alignment with corporate reporting requirements Technical Leadership & Delivery Coordination: Create and manage Azure DevOps work items, QA tasks, sprint planning, and release activities Coordinate development, QA, and deployment across data engineers, analysts, and BI developers Guide the team on data fixes, release readiness, and testing priorities Act as a central point for resolving blockers and accelerating delivery across cross‑functional teams Participate actively in daily scrum ceremonies, sprint reviews, and delivery planning Data Quality, Validation & Issue Resolution:



Guide the Data team to investigate and resolve data quality issues including mismatches, missing records, schema changes impacting pipelines, and large‑volume data failures Drive sanity checks, validation strategies, and QA alignment across the team Ensure production data accuracy and consistency for business reporting and analytics Respond to and resolve production incidents, refresh failures, and stakeholder‑reported data issues Stakeholder Support & Data Enablement: Serve as the primary technical expert for business users seeking to understand dataset structure, column definitions, and correct usage of curated datasets Guide stakeholders in selecting between raw and curated data layers based on their requirements Support integration requests from downstream applications by providing dataset scoping, documentation, and access Translate business requirements into actionable data architecture decisions and dataset deliverables Data Governance & Security: Implement and advise on enterprise data access controls, Row‑Level Security (RLS) models, and security rules applied via dimension tables and Power BI semantic layers Manage dataset access provisioning for users and service accounts Maintain and evolve standardized security models, governance practices, and the Orb security toolkit Documentation & Standards: Author and maintain enterprise‑wide technical documentation including database naming conventions, data architecture diagrams, and dataset mapping documents Define and enforce object naming conventions for databases, schemas, tables, views, columns, indexes, and foreign keys across the Orb platform Ensure documentation is kept current through active revision cycles Data Platform & Architecture: Microsoft Azure - Azure Data Factory (ADF), Azure Synapse Analytics, Azure Data Lake Microsoft Fabric - Lakehouse, Data Warehouse, shortcuts, capacity planning, One Lake security Data Platform Concepts - medallion architecture (raw, integrated/ODS, curated layers), delta mode processing Star Schema/Dimensional Modelling - fact/dimension design, foreign key normalization, partition strategies SQL Server/Azure SQL Database - schema design, views, stored procedures, indexes,



constraints Business Intelligence & Reporting: Microsoft Power BI – semantic model design, Row‑Level Security (RLS), DAX, Direct Query, shared datasets, Power BI Service Azure Analysis Services – tabular models, semantic layers Data Engineering & Integration: Azure Data Factory (ADF) – ETL/ELT pipelines, data flows, triggers, CI/CD Profisee – Master Data Management (MDM) tooling, data mastering workflows Delta Lake – medallion architecture (bronze/silver/gold layers) Source‑to‑Raw (R2I) Mapping – data mapping, profiling, transformation rules DevOps & Project Management: Azure DevOps – work item management, sprint planning, release pipelines, repository management, Git integration Data Governance & Modelling Tools: Profisee – MDM governance workflows TOAD – database development and SQL querying JSON – configuration files, rule‑based filtering logic in Power BI Collaboration & Communication: Microsoft Teams – daily stand‑ups, cross‑functional coordination, stakeholder communications Microsoft Outlook/M365 – enterprise communication and documentation Demonstrated experience delivering enterprise data platforms in a cloud‑based environment (Azure preferred). 15+ years of progressive experience in data architecture, data modelling, or a senior data analyst role. Proactive problem‑solving with a focus on data quality and accuracy. Proven track record of leading data governance and documentation initiatives. Strong organizational and delivery management skills. Excellent SQL skills and ability to design efficient views, joins, and indexing strategies. Member of the Canadian or Global Leadership Team: This position requires knowledge of a language other than French, namely English, as it involves collaboration with members of the Canadian or global leadership team located outside Québec. Bachelor’s degree in computer science, Information Systems, Data Engineering, or a related technical field. Experience with financial and project management data domains (ERP systems such as Oracle EBS is a strong asset). Experience working in Agile/Scrum delivery environments with Azure DevOps. Bilingual (English/French). Solid expertise in dimensional modelling, star schema design, and database normalization. Ability to communicate technical concepts clearly to non‑technical business stakeholders. Deep understanding of ETL/ELT pipeline architecture and data lake medallion patterns. Master’s degree is an asset. #J-18808-Ljbffr

📌 Data Information Architect (Toronto)
🏢 AtkinsRéalis
📍 Toronto