Principal Data Architect

Job summary

Assess existing data, integration, BI, and AI platforms, then define target architectures, migration strategies, and phased modernization roadmaps. Validate recommendations through technical reviews and proofs of concept, identify AI automation opportunities, and communicate implementation plans, risks, costs, and guidance to client stakeholders and engineering teams.

Job details

Position: Principal Data & AI Architect / Senior Consultant Location: Remote Duration: 6-12 months Client is based out of Canada and looking for people based out of Canada only Role Overview Lead As-Is assessments and define validated To-Be architectures and modernization roadmaps across enterprise data, analytics, BI and AI platforms. Validate recommendations through hands-on technical assessments, code and architecture reviews, PoCs, and implementation feasibility analysis. Define migration strategies, technology choices, required skills, implementation plans and opportunities to use AI for automation and productivity improvements. Required Technical Experience Overall experience: 12–15+ years in data engineering, architecture, analytics platforms or technology modernization, including senior architect or technical leadership responsibilities. Azure Data Platform: 5+ years of hands-on experience with Azure data services, including ADLS Gen2, Azure Data Factory (ADF), Azure Synapse Analytics and Azure SQL. Microsoft Fabric: 2+ years of hands-on experience with Fabric architecture and implementation, including OneLake, Lakehouse, Warehouse, Data Factory, pipelines, notebooks and semantic models. Data Architecture: 5+ years designing enterprise data platforms, lakehouse and medallion architectures (Bronze/Silver/Gold), data models, ETL/ELT pipelines, data quality and governance. ETL and Data Integration: 5+ years with enterprise integration technologies, including Informatica (PowerCenter/IDMC), ADF or equivalent ETL/ELT platforms. Experience modernizing legacy integration workloads is essential. BI and Reporting: 5+ years with enterprise BI platforms such as Power BI, Tableau and/or Cognos. Strong understanding of semantic models, dimensional modeling, report dependencies, security and performance optimization. Platform Migration: Demonstrated experience assessing and executing data or analytics migrations, preferably Synapse to Fabric, Cognos to Power BI, and Informatica to modern cloud-native data platforms. AI/GenAI and Automation: 2+ years of practical experience with GenAI/LLM solutions, including identifying and implementing opportunities for AI-assisted engineering, code conversion, metadata analysis, documentation, test generation and migration automation. Agentic AI: Hands-on architecture or implementation experience with Azure AI Foundry, LLM orchestration, RAG, tool calling and agentic workflows. Ability to assess when agent-based automation is appropriate. Kubernetes and Cloud-Native Architecture: 2+ years of experience with Kubernetes, containers, APIs, CI/CD and cloud-native deployment patterns, preferably for AI services or agentic applications. DevOps and Infrastructure Automation: Experience with Git, CI/CD, infrastructure as code (Terraform or equivalent), automated testing, environment promotion and production deployment practices. Security and Governance: Experience with enterprise data security, identity and access management, metadata, lineage, data quality, compliance and AI governance. Key Responsibilities Assess existing data, ETL, BI and AI platforms through architecture reviews, source-code analysis, stakeholder discussions and hands-on technical investigation. Define target-state architectures, technology recommendations, migration approaches and phased implementation roadmaps. Develop PoCs to validate migration feasibility, platform capabilities, performance, cost and technical risks. Identify opportunities to use AI to automate legacy code conversion, ETL migration, report modernization, testing, documentation and data validation. Define architecture patterns and implementation guidance for Synapse-to-Fabric migration, Cognos-to-Power BI modernization and agentic AI solutions using Azure AI Foundry and Kubernetes. Estimate implementation effort, required skills, dependencies, risks, costs and expected benefits. Communicate findings and recommendations clearly to client stakeholders and guide engineering teams during implementation handoff. Preferred Qualifications Direct experience delivering Synapse-to-Fabric migrations, Cognos-to-Power BI modernization or Informatica migration programs. Experience building reusable AI-powered migration accelerators and automated testing or reconciliation frameworks. Microsoft Azure, Fabric, Power BI, Azure AI or relevant architecture certifications. Experience with Databricks, Spark, streaming/CDC, advanced data governance or enterprise-scale AI deployments.

What you’ll do

Assess existing data, integration, BI, and AI platforms, then define target architectures, migration strategies, and phased modernization roadmaps. Validate recommendations through technical reviews and proofs of concept, identify AI automation opportunities, and communicate implementation plans, risks, costs, and guidance to client stakeholders and engineering teams.

Requirements

Requires 12–15+ years of experience in data engineering, architecture, analytics platforms, or technology modernization, including senior technical leadership, with substantial hands-on experience in Azure data services, Microsoft Fabric, enterprise data architecture, ETL/ELT, and BI. Also requires practical experience with GenAI and agentic AI, Kubernetes and cloud-native patterns, DevOps and infrastructure automation, security and governance, and data or analytics platform migrations.

Listed skills

• Power BI · Preferred
• Kubernetes · Preferred
• CI/CD · Preferred

Other relevant skills

Identified from the job description. Confirm important requirements above.

• Azure Data Platform
• Microsoft Fabric
• Data Architecture
• ETL/ELT
• Informatica
• Power BI
• Data Migration
• Generative AI
• Azure AI Foundry
• Agentic AI
• Kubernetes
• Cloud-Native Architecture
• CI/CD
• Infrastructure as Code
• Data Governance
• Enterprise Architecture

Job areas

• Technology
• Data & Analytics
• Software
• Consulting
• Management & Leadership

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