Data Engineer, Marketplace
Lyft
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Compensation
Salary & market context
45% above the BLS national median
BLS national median: $74,680
- $135,000
- Additionally, hybrid roles have the flexibility to work from anywhere for up to 4 weeks per year. #Hybrid The expected base pay range for this position in the Toronto area is CAD $108,000 - CAD $135,000, not inclusive of potential equity offering, bonus or benefits.
Requirements
Top requirements
- 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 engineering as a hands-on Individual Contributor delivering features end-to-end Proven ability to collaborate with cross-functional stakeholders (analytics, science, product, and engineering) to align data solutions with business objectives Proficient in data validation, analysis, and visualization for clear insight presentation Skilled in designing complex data models and resilient data pipelines, with solid understanding of analytical data modeling Expertise in advanced SQL, capable of understanding intricate business logic and implementing custom solutions Strong algorithmic foundation and hands-on coding skills in Python, Java, or similar languages Deep understanding of MPP systems and hands-on experience with ETL in Spark or similar technologies Familiarity with data system design principles for data-intensive applications Practical experience with workflow management tools (e.g., Airflow, Flyte, etc.) Benefits: Extended health and dental coverage options, along with life insurance and disability benefits Mental health benefits Family building benefits Child care and pet benefits Access to a Lyft funded Health Care Savings Account RRSP plan with company match to help save for your future In addition to provincial observed holidays, salaried team members are covered under Lyft's flexible paid time off policy.
- Salary ranges are dependent on a variety of factors, including qualifications, experience and geographic location.
Perks & setup
Benefits candidates care about
- s:
- Extended health and dental coverage options, along with life insurance and disability benefits
- Mental health benefits
- Family building benefits
Why candidates care
Benefits & perks
- s:
- Extended health and dental coverage options, along with life insurance and disability benefits
- Mental health benefits
- Family building benefits
- Child care and pet benefits
- Access to a Lyft funded Health Care Savings Account
- RRSP plan with company match to help save for your future
- In addition to provincial observed holidays, salaried team members are covered under Lyft's flexible paid time off policy. The policy allows team members to take off as much time as they need (with manager approval). Hourly team members get 15 days paid time off, with an additional day for each year of service
Start here
Requirements
- 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 engineering as a hands-on Individual Contributor delivering features end-to-end Proven ability to collaborate with cross-functional stakeholders (analytics, science, product, and engineering) to align data solutions with business objectives Proficient in data validation, analysis, and visualization for clear insight presentation Skilled in designing complex data models and resilient data pipelines, with solid understanding of analytical data modeling Expertise in advanced SQL, capable of understanding intricate business logic and implementing custom solutions Strong algorithmic foundation and hands-on coding skills in Python, Java, or similar languages Deep understanding of MPP systems and hands-on experience with ETL in Spark or similar technologies Familiarity with data system design principles for data-intensive applications Practical experience with workflow management tools (e.g., Airflow, Flyte, etc.) Benefits: Extended health and dental coverage options, along with life insurance and disability benefits Mental health benefits Family building benefits Child care and pet benefits Access to a Lyft funded Health Care Savings Account RRSP plan with company match to help save for your future In addition to provincial observed holidays, salaried team members are covered under Lyft's flexible paid time off policy.
- Salary ranges are dependent on a variety of factors, including qualifications, experience and geographic location.
Responsibilities
What you'll do
- s:
- 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
Role snapshot
About the role
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.
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