Data Engineer Sr

Requisition Number: 106522  Data Engineer Sr Location This role is hybrid, with the onsite locations in Montreal, QC, Canada or Toronto, ON, Canada. Salary: $120,000 –$ 140,000 CAD annualized 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 We are seeking a Senior Data Engineer to design, build, and optimize modern data platforms that enable analytics, reporting, operational intelligence, and AI-driven solutions. In this role, you will work across the full data lifecycle, developing scalable data pipelines, integrating complex data sources, and delivering high-quality data solutions that support business and customer objectives. You will collaborate with architects, engineers, analysts, and stakeholders to modernize data environments and implement cloud-based data platforms. The ideal candidate is both a strong technical practitioner and a problem solver who enjoys working with modern data technologies, navigating ambiguity, and delivering scalable solutions in dynamic environments. Key Responsibilities Design, develop, and maintain scalable data pipelines that ingest, transform, and deliver data from structured, semi-structured, and unstructured sources. Build and support ETL/ELT solutions across cloud-based data platforms, data warehouses, lakehouses, and analytics environments. Develop data integration frameworks that enable reliable, secure, and efficient movement of data across systems. Design and implement dimensional models, transformation logic, and data structures that support analytics, reporting, and AI initiatives. Work with modern cloud data technologies such as Microsoft Fabric, Databricks, Snowflake, and related platforms. Collaborate with architects and stakeholders to translate business requirements into scalable technical solutions. Apply data quality, testing, monitoring, lineage, and governance best practices throughout the development lifecycle. Optimize data pipelines and data platforms for performance, scalability, reliability, and cost efficiency. Support modernization initiatives involving legacy data platforms, data warehouses, and integration technologies. Implement modern engineering practices including source control, automated testing,…