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Salary: CAD 171,000 - 235,500 / annual
Faire is a technology wholesale platform connecting independent retailers globally with suppliers and products. The company uses data, AI, and machine learning to power a multi-hundred-billion-dollar wholesale market that has historically been fragmented and offline.
You will serve as a technical leader on the analytics and data engineering team, working closely with Data Scientists, Product Analysts, and Software Engineers to design and build data capabilities that inform product launches and roadmaps. This role focuses on leveraging AI to streamline data pipeline development, improve data consumption workflows, and automate routine analytical tasks. You'll see direct impact between your work and company growth, user satisfaction, and product outcomes.
Key responsibilities include:
- Lead cross-team and multi-phase projects from design through implementation, fostering collaboration with cross-functional partners
- Lead technical execution in building scalable data models and pipelines, defining architecture, feature requirements, and roadmap
- Build data pipelines with rigorous approaches to data quality, validation, testing, and observability
- Embed AI into daily workflows to redefine how data systems are built, maintained, and scaled
- Optimize processes for operational excellence in project management and system reliability
- Ensure security standards and data quality standards are met within data systems and workflows
- Embrace emerging technologies with enthusiasm
You'll work with one of the richest datasets in the world, use cutting-edge technology, and collaborate with A-tier players. The role is hybrid in Toronto, with employees in office 3 days per week (Tuesdays, Thursdays, and one flex day) and flexibility to work remotely up to 4 weeks per year.
Requirements:
- 4+ years of experience in analytics and data engineering roles focused on data modeling, large-scale data processing, and tool development for analytics or data science use cases
- Demonstrated communication and leadership skills with a history of initiating and steering successful projects across multiple stakeholders
- Production-level development experience in Python
- Strong SQL skills with demonstrable competencies in designing well-architected data models and optimizing query performance
- Deep experience and knowledge of data warehousing concepts, ETLs, big data technologies, and analytics platforms
- Experience with Airflow, Docker, DBT, or similar analytics workflow tools
- BA/BS degree in Computer Science, Math, Physics, or a related technical field
