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 effective 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 solid asset). Experience working in Agile/Scrum delivery environments with Azure DevOps. Bilingual (English/French). Strong 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.

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📌 Data Information Architect (Ontario)
🏢 AtkinsRéalis
📍 Ontario