Data Engineer, Marketplace

Benefits

Parental leave

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Non-birth-parent leave

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Family-building benefits

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• Adoption assistance: Not verified
• Surrogacy assistance: Not verified

Mental health support

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Relocation assistance

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Childcare support

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Learning budget

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Verification

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Salary

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Market context

U.S. role benchmark (BLS OEWS)

$111,944 U.S. median for this role

Projected growth (BLS Employment Projections)

+13.7% - Much faster than average

Matched to SOC 15-1252 - Data and ML aggregate by role bucket.

Source: U.S. Bureau of Labor Statistics, OEWS, May 2024 and Employment Projections, 2024-2034.

Role

Role function

Data From the posting source

Seniority

Mid From the posting source

Schedule

Shift type

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Weekend work

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Company

Equity

Offered Verified - SEC 10-K source

Application

Cover letter

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Assessment

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Deadline

Not stated

Where they hire

State eligibility is not yet verified.

About this role

Data Engineer, Marketplace Toronto, Canada 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

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