Computer Science jobs in Canada

The Principal Data Engineer/Technical Lead is a role that requires technical depth, exceptional project strategy and strong communication skills.

We’re looking for a Principal Data Engineer who thrives at the intersection of hands-on engineering and technical leadership. You will oversee a Principal Data Architect and partner on architectural decisions as well as oversee the implementation of our modern data platform. This is a highly impactful role where you'll support with release management, own data projects and optimize the data ecosystem for performance, scale, and cost efficiency.

This role is based in Canada.

• Technical and Team Leadership
  • Manage a team of 2-3 (Data Engineers and a Principal Architect).
  • Oversee and manage major data projects and initiatives.
  • Partner with Engineering and other development technical leads to understand roadblocks, gaps in knowledge, core competencies and opportunities to improve data access and usability.
  • Perform data specific peer code reviews.
• Technical Strategy & Architecture
  • Oversee the end-to-end architecture of the modern data stack—covering ingestion, transformation, storage, and analytics.
  • Set direction for scalable, modular data pipelines using tools like Airbyte, dbt, Sisense, and Snowflake.
  • Define and enforce best practices for SDLC, CI/CD, version control, and data testing within the team.
  • Partner with product, analytics, and platform teams to design future-proof data models and infrastructure.
• Platform Ownership & DataOps
  • Oversee ingestion pipelines (Airbyte/ADF), data transformation (dbt), and warehousing (Snowflake).
  • Drive DataOps maturity—automated testing, CI/CD pipelines, monitoring, and deployment workflows.
• Infrastructure, Vendor, and Cost Optimization
  • Support in managing vendor relationships, tool evaluations, contract renewals, and performance assessments.
  • Continuously assess and improve infrastructure reliability, resilience, and operational efficiency.

• Bachelor’s degree in computer science, Engineering, or related technical discipline

• 10+ years of experience in data engineering and data architecture, with 2+ years’ experience as a technical lead.
• Professional, hands-on work experience (5 years) with Snowflake, dbt, and Azure Data Factory (ADF).
• Experience balancing hands-on execution with technical leadership, mentoring, and cross-functional collaboration.
• Strong SQL skills with advanced knowledge of Joins, Unions, CTEs, Aggregations, Lag/Lead, and optimization techniques.
• Proficiency in Python for data manipulation, scripting, and automation.
• Demonstrated experience in data modeling, including dimensional and modern approaches (Star, Snowflake, OWD).
• Hands-on experience in building and maintaining data pipelines (ETL/ELT).
• Understanding of cost optimization, caching, partitioning, and indexing strategies for performance tuning.
• Familiarity with BI tools such as Power BI, Sisense, Looker, Tableau, and Domo.
• Experience with customer personalization solutions and handling large datasets.
• Exposure to scripting languages like Python, Perl, or Shell.

• Ownership: Technical Lead with a strong sense of accountability for data warehouse reliability, security, and performance. Defines clear expectations and processes, fosters team autonomy, and supports the development of future leaders. Acts as the escalation point for complex decisions and operational tradeoffs.
• Curiosity: Drives improvement by identifying new technologies, tools, and practices. Encourages the team to challenge assumptions and implement innovations that align with platform and business goals.
• Resilience: Provides steady leadership through incidents and change. Anticipates risks, maintains focus under pressure, and strengthens the team’s ability to deliver in high-stakes or uncertain situations.
• Collaboration: Leads alignment across teams by building strong partnerships and driving shared outcomes. Communicates technical direction clearly to diverse audiences and ensures coordinated execution.
• Technical Proficiency: Applies deep dbt and Snowflake, infrastructure and DevOps expertise to guide technical decisions. Ensures solutions meet performance and security standards, and mentors the team to raise technical quality.