Senior Manager Data & AI Technical Strategy Lead

Role overview

Architecture and delivery

• Lead current-, transition-, and target-state data architectures across cloud, hybrid, operational, analytical, and real-time environments.
• Guide data platform, ingestion, streaming, integration, modelling, lakehouse, warehouse, and data-product patterns.
• Oversee multiple projects and teams; review designs, specifications, estimates, implementation plans, testing, and operational readiness.
• Facilitate discovery, workshops, design reviews, technical decisions, and stakeholder presentations; identify risks and mitigation options.
• Support Agile requirements, backlogs, acceptance criteria, architecture governance, release planning, and complex technical escalations.

Governance, identity, and analytics

• Lead or support data governance, metadata, cataloguing, lineage, quality, stewardship, classification, retention, and access controls.
• Guide master and reference data management, identity resolution, matching, survivorship, deduplication, and golden-record creation.
• Guide reporting, Power BI semantic models, reusable datasets, dashboards, and modernization of legacy analytics platforms.
• Ensure solutions support privacy, security, auditability, accessibility, regulatory obligations, reliability, and cost management.

Leadership and business growth

• Coach technical and delivery professionals; support resource planning, onboarding, capability development, and a strong technical culture.
• Advise client executives and align Data and AI initiatives with business priorities and modernization roadmaps.
• Shape opportunities and support presales, solution development, estimates, proposals, commercial discussions, and mobilization.
• Develop market offerings, reusable architectures, accelerators, demonstrations, and sales assets; build technology-partner relationships.

Experience and leadership qualifications

• 15+ years across data warehousing, data engineering, migration and modernization, architecture, AI, machine learning, data science, advanced analytics, or related technology consulting.
• Established Data and AI credibility and experience engaging senior business and technology executives.
• Consulting, professional services, technology advisory, systems integration, or comparable client-facing experience.
• Proven opportunity origination, presales, business development, solution selling, or consulting sales success.
• Experience shaping and delivering complex Data and AI programs and expanding strategic client relationships.
• Strong understanding of generative AI, large language models, agentic AI, multi-agent solutions, enterprise AI adoption, and AI-enabled processes.
• Strong executive communication, facilitation, storytelling, negotiation, presentation, commercial judgment, and delivery leadership.

Technology and domain experience

• Core data disciplines include enterprise warehousing, dimensional modelling, Microsoft Fabric, OneLake, Purview, Power BI, Azure data services, and Microsoft AI services.
• Relevant areas include generative AI, retrieval-augmented generation, agentic systems, data pipelines using Spark, Python, SQL, and Databricks.
• Additional areas include master and reference data, identity resolution, governance, metadata, data quality, modelling, and enterprise integration patterns.
• Broader experience may include Dynamics 365, Dataverse, Power Platform, APIs, microservices, DevSecOps, CI/CD, observability, cloud architecture, and responsible AI.
• Must be able to work hands-on in core data disciplines while maintaining enough breadth to guide technical decisions and ensure commitments are executable.

Compensation

• The posting lists CAD 177,500–210,800 for British Columbia/Ontario and states compensation varies with location, role, skills, and experience.
• The compensation range is described as based on full-time employment; a pay cadence is not stated.