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Senior Product Analytics Engineer

🇨🇦Faire

Toronto, ON0 applicants
Full TimeSenior

Job Description

About Faire Faire is a technology wholesale platform built on the belief that the future is local. Independent retailers around the globe collectively represent a multi-hundred-billion-dollar wholesale market that has historically been fragmented and offline. At Faire, we're using the power of tech, data, and machine learning to connect this thriving community of entrepreneurs across the globe. Picture your favorite boutique in town — we help them discover the best products from around the world to sell in their stores. With the right tools and insights, we believe that we can level the playing field so businesses can grow and local communities can thrive. We’re looking for smart, resourceful and passionate people to join us as we power the shop local movement. If you believe in community, come join ours. About the role Are you passionate about using data and AI to shape the future of Faire's product features for small and medium businesses (SMBs)? If so, we want to talk to you! We're looking for a technical leader in our team to work closely with Data Scientists, Product Analysts and Software Engineers to support product launches and roadmaps by designing and building data capabilities that inform and drive insights. You will lead the path in using AI to boost productivity and transform how analytical engineering operates—leveraging AI to streamline data pipeline development and operations, improve data consumption workflows, and automate routine analytical tasks. In this role, you'll see a direct link between your work, company growth, and user satisfaction. You'll work with A tier players, work with one of the richest data sets in the world, use cutting-edge technology, and see your efforts affect products and SMBs regularly. Join us and be part of a team that values data-driven innovation and excellence. What You Will Do The ideal candidate will possess a perfect blend of analytics and data engineering expertise, along with strong skills in developing and supporting large-scale, high-performance data storage and processing systems. They should have a proven track record of collaborating with key stakeholders to execute on company-wide data initiatives. Lead cross-team and/or multi-phase projects from design through implementation, fostering collaboration with cross-functional partners. Lead the technical execution in building scalable data models and pipelines for a domain defining the architecture, feature requirements, roadmap. Build data pipelines with rigorous approaches to data quality, validation, testing, and observability. Redefine how we build, maintain, and scale data systems by embedding AI into our daily workflows. Optimize processes for operational excellence in project management and system reliability.

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