Data​/Information Architect

Job Description Overview

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.

• 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).

• 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.

• Create and manage Azure Dev Ops 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, and act as a central point for resolving blockers.
• Participate actively in daily scrum ceremonies, sprint reviews, and delivery planning.

• Guide the team to investigate and resolve data quality issues, including mismatches, missing records, schema changes, 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.

• 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.

• 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.

• 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.

• Microsoft Azure – Azure Data Factory (ADF), Azure Synapse Analytics, Azure Data Lake.
• Microsoft Fabric – Lakehouse, Data Warehouse, shortcuts, capacity planning, One Lake security.
• Data…