Data Architect

AI Data Architect Location This is a hybrid work opportunity in our Toronto, ON office.

Salary:
$140,000
- $160,000 CAD annually Insight at a Glance
- 14,000+ engaged teammates globally
- $8.2 billion in revenue in 2025
- Certified as a Great Place to work in 9 Countries in 2025
- Fortune 500 Company (No. 447) in 2025
- Received 25+ industry and partner awards in the past year
- $1.4M+ total charitable contributions in 2024 by Insight globally Now is the time to bring your expertise to Insight. We are not just a tech company; we are a people‑first company. We believe that by unlocking the power of people and technology, we can accelerate transformation and achieve extraordinary results. As a Fortune 500 Solutions Integrator with deep expertise in cloud, data, AI, cybersecurity, and intelligent edge, we guide organizations through complex digital decisions.

About the Role
As a Data Architect, you will serve as a senior technical leader responsible for designing modern data strategies, target‑state architectures, and scalable data platforms that enable analytics, AI, and business transformation. This position combines architecture leadership, customer consultation, solution design, and technical advisory responsibilities. You will help organizations assess their current data landscape, define future‑state architectures, and guide the implementation of modern cloud‑based data solutions that support governance, analytics, AI readiness, and long‑term scalability. The ideal candidate brings deep expertise in modern data platforms, strong consulting and stakeholder management capabilities, and a passion for solving complex business challenges through data. You are equally comfortable discussing strategy with business leaders, designing architectural roadmaps, and partnering with engineering teams to deliver practical solutions.

Key Responsibilities
- Design and lead modern data architectures that support analytics, business intelligence, machine learning, and AI-driven use cases.
- Define target‑state data architectures, including data models, semantic layers, integration patterns, governance frameworks, and platform strategies.
- Assess current‑state data environments and develop pragmatic modernization, migration, and implementation roadmaps.
- Translate business objectives and technical requirements into scalable data solutions that support reporting, analytics, operational decision‑making, and AI enablement.
- Design unified data models, dimensional models, semantic layers, and analytics‑ready data structures that drive consistency and usability across large‑scale data environments.
- Serve as a thought leader for data governance, data lineage, data quality, metadata management, and data product strategies.
- Lead architecture workshops, discovery sessions, and technical discussions with business and technology stakeholders.
- Provide architectural guidance and quality oversight for delivery teams, including data engineers and implementation resources.
- Partner with engineering teams to ensure architecture decisions are effectively implemented while maintaining security, performance, scalability, and governance standards.
- Support qualified customer opportunities through discovery activities, solution design, proof‑of‑concept development, technical presentations, and proposal support.
- Develop architecture artifacts, high‑level designs, implementation approaches, estimates, and technical recommendations.
- Advise customers on modern cloud data platforms and architectures including Microsoft Fabric, Databricks, Snowflake, AWS, Google Cloud, and related technologies.
- Design data foundations that support advanced analytics, machine learning, generative AI, knowledge management, and AI‑enabled business solutions.
- Evaluate emerging technologies and recommend architecture approaches that align with business goals and long‑term growth strategies.
- Mentor and coach technical team members while promoting architecture standards, best practices, and continuous learning.
- Balance advisory, architecture, delivery, and customer engagement responsibilities while effectively managing competing priorities and evolving requirements. What We're Looking For Required Qualifications Required Qualifications
- Minimum eight (8) years of experience in Data Architecture, Data Engineering, Analytics Architecture, Enterprise Architecture, or related technical disciplines.
- Strong experience designing modern cloud‑based data platforms, dimensional data models, semantic layers, data integration patterns, and analytics‑ready architectures.
- Experience defining target‑state architectures, assessing current‑state environments, and leading modernization or migration initiatives.
- Experience with cloud‑based data platforms and technologies such as Microsoft Fabric, Databricks, Snowflake, Azure Data Factory, Synapse, AWS Redshift, Google BigQuery, or comparable solutions.
- Strong understanding of modern data warehous