Director, Data Engineering and AI
- Toronto, ON
- Hybrid
- Posted Sep 18, 2026
- 1 position
$130,000–$180,000 / year
Opens an external site
- Employment type
- Full-time
- Experience level
- Lead · 10+ years
- Apply by
- Oct 11, 2026
- Posting language
- English
- Working hours
- 40 hours per week
- Office presence
- 3 days per week
- Seniority
- Director
- Application method
- Direct apply is available
Job summary
Lead the development of a unified Microsoft Azure data platform and governance framework for a financial sector client. Design and implement applied AI solutions, automation, and reporting capabilities using the Microsoft ecosystem.
Job details
Our client in the financial sector is seeking a fulltime Director, Data Engineering & AI to lead the development of its data platform, governance framework, analytics capabilities, and applied AI solutions. This is a hands-on leadership position, with approximately 80% of the role focused on data/AI architecture, design and engineering and 20% on data strategy and governance. The successful candidate will build an integrated Microsoft-based data environment while developing the organization’s capabilities around AI agents, automation, structured and unstructured data, and responsible AI. Location: Hybrid 3d/week downtown Toronto Responsibilities Build and lead a unified Microsoft Azure data and reporting platform integrating Dynamics 365, Dataverse, SharePoint, Teams, Microsoft Fabric, and other enterprise data sources. Design and implement scalable data architecture, pipelines, integrations, and reporting solutions. Establish metadata, taxonomy, content ontology, data quality, governance, and privacy standards using Microsoft Purview. Deliver Power BI reporting and self-service analytics capabilities. Develop solutions for structured, semi-structured, and unstructured information including documents, images, PDFs, and call recordings. Leverage Azure AI Document Intelligence, Azure AI Speech, Azure AI Search, and related Microsoft technologies. Build an AI-ready data foundation and deliver applied AI and automation solutions using Microsoft 365 Copilot, Copilot Studio, Azure AI Foundry, and Power Automate. Apply AI to use cases including transcription, summarization, sentiment analysis, entity extraction, image understanding, and document understanding. Partner with business leaders to identify and prioritize AI agent opportunities. Establish practical standards to ensure AI solutions are secure, responsible, scalable, and reliable. Lead and develop a small data and AI team as the function grows. Requirements 8+ years of experience in data engineering, data platforms, or related roles within the Microsoft ecosystem. Strong hands-on experience with Azure data services, Microsoft Fabric, Azure SQL, Dataverse, and Power BI. Experience integrating Dynamics 365 and SharePoint as enterprise data sources. Proven experience designing and building cloud data platforms, pipelines, and governance capabilities. Experience working with structured, semi-structured, and unstructured data at scale. Experience with document processing, OCR, speech-to-text, summarization, sentiment analysis, and/or entity extraction. Experience creating AI-ready data foundations and delivering practical AI agent solutions. Experience with Microsoft 365 Copilot, Copilot Studio, Azure AI Foundry, Power Automate, or related technologies. Experience using open-source technologies within Azure while maintaining enterprise data within the Microsoft environment. Strong leadership, problem-solving, communication, and stakeholder-management skills. Experience operating in a regulated, privacy-sensitive, financial services, or similar environment is an asset. Relevant Microsoft data, AI, machine learning, or cloud certifications are an asset. French/English bilingualism is an asset.
What you’ll do
Lead the development of a unified Microsoft Azure data platform and governance framework for a financial sector client. Design and implement applied AI solutions, automation, and reporting capabilities using the Microsoft ecosystem.
Requirements
Requires 8+ years of experience in data engineering within the Microsoft ecosystem, specifically with Azure, Fabric, and Power BI. Proven expertise in building AI-ready data foundations and managing structured and unstructured data is essential.
Listed skills
- Microsoft Azure · Preferred
- Power BI · Preferred
- Stakeholder Management · Preferred
Other relevant skills
Identified from the job description. Confirm important requirements above.
- Data Engineering
- AI Architecture
- Microsoft Azure
- Microsoft Fabric
- Power BI
- Data Governance
- Azure AI Foundry
- Copilot Studio
- Power Automate
- Dataverse
- Dynamics 365
- Microsoft Purview
- Azure AI Search
- OCR
- Sentiment Analysis
- Stakeholder Management
Job areas
- Data & Analytics
- Technology
- Management & Leadership
- Software
- Finance & Accounting
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