Data Engineer, Marketplace
Lyft · Toronto, Canada
Experience: 3+ years
At Lyft, our purpose is to serve and connect. We aim to achieve this by cultivating a work environment where all team members belong and have the opportunity to thrive. Here at Lyft, data is at the core of every decision we make. It powers our business — helping us create great transportation experiences for our customers and providing insights into the effectiveness of our product launches and features. As a Data Engineer on Lyft’s Marketplace – Decision Apps team, you will own and evolve the data pipelines that power our top-line financial, pricing, and driver-related metrics. You will collaborate with Analytics, Data Science, and Engineering partners to design data models and architectures — proposing innovative ideas, evaluating multiple approaches, and implementing solutions grounded in fundamental engineering principles and rigorous data analysis. Your work will provide seamless access to the insights that drive Lyft’s success. Responsibilities: Take ownership of core data pipelines, ensuring resilience, optimal performance, timely delivery, data quality, and seamless onboarding of new features Continuously evolve data models and schemas to meet business and engineering requirements Implement and maintain systems to monitor and enhance data quality and consistency Develop tools that support self-service management of data pipelines (ETL) and perform SQL tuning to optimize data processing performance Contribute to the Data Engineering team’s technical roadmap, ensuring alignment with team and stakeholder goals Write clean, well-tested, and maintainable code, prioritizing scalability and cost efficiency Conduct code reviews to uphold code quality standards and facilitate knowledge sharing Participate in on-call rotations to maintain high availability and reliability of workflows and data pipelines Collaborate with internal and external partners to remove blockers, provide support, and achieve results Experience: 3+ years of professional experience in data engine