Data Engineer
Lyft is hiring a Data Engineer in Toronto, Canada. It pays $108k a year and Level rates it ; you can apply on Lyft.
Level's read on this job
- Works on AI ●●●○ is how Level rates this data engineer role: the daily work is on AI products, without building the model.
- The posting mentions Spark, Python and SQL among its tools and skills.
- Level classes it as a senior role.
- Lyft has 169 other open roles on Level.
AI in this role
Own core data pipelines and data models powering associate and AI agent platforms for customer care and safety.
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.
The Safety and Customer Care (SCC) team at Lyft manages over 1.7 million monthly human and AI interactions and serves as Lyft's primary direct touchpoint with riders and drivers. We handle critical infrastructure that powers both human associates and AI agents to make riders and drivers feel safe and comfortable while riding or driving with Lyft, transforming every support interaction into a moment of genuine connection.
As a Data Engineer on the SCC team, you will have ownership over the data modeling and pipelines that power SCC’s Associate and AI Agent Platform . Your efforts will be critical to the reliability of our pipelines, execution of third party data integrations, accurate reporting of agents performance, and efficiency improvements that can save millions of dollars / year. You will work cross-functionally to bridge Lyft's business goals with data engineering. Your efforts will allow access to business and user behavior insights, using huge amounts of Lyft data to fuel several teams such as Analytics, Data Science, Engineering, and many others.
Responsibilities:
- Owner of the core data pipeline, responsible for scaling up data processing flow to meet the rapid data growth at Lyft
- Evolve data model and data schema based on business and engineering needs
- Implement systems tracking data quality and consistency
- Develop tools supporting self-service data pipeline management (ETL)
- SQL and MapReduce job tuning to improve data processing performance
- Write well-crafted, well-tested, readable, maintainable code
- Participate in code reviews to ensure code quality and distribute knowledge
- Collaborate cross-functionally with product, engineering, data science, and marketing teams to understand business problems and align on prioritization and solutions
Experience:
- Bachelor's degree in Computer Science, Engineering, Mathematics, Statistics, or a related field
- 4+ years of professional experience in data engineering, ideally with large-scale distributed systems.
- Strong skills in Spark, Python (or similar scripting language), and SQL performance tuning
- Experience with AWS, Hadoop/S3, Hive, Presto, Airflow, and related tools
- Solid understanding of ETL processes, workflow orchestration, and data warehousing
- A collaborative mindset—you’re comfortable working across teams to solve real-world problems
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. 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
- Lyft is proud to support new parents with 18 weeks of paid time off, designed as a top-up plan to complement provincial programs. Biological, adoptive, and foster parents are all eligible.
- Subsidized commuter benefits and Lyft ride credits
Lyft is committed to creating an inclusive workforce that fosters belonging. Lyft believes that every person has a right to equal employment opportunities without discrimination because of race, ancestry, place of origin, colour, ethnic origin, citizenship, creed, sex, sexual orientation, gender identity, gender expression, age, marital status, family status, disability, pardoned record of offences, or any other basis protected by applicable law or by Company policy. Lyft also strives for a healthy and safe workplace and strictly prohibits harassment of any kind. Accommodation for persons with disabilities will be provided upon request in accordance with applicable law during the application and hiring process. Please contact your recruiter if you wish to make such a request.
Lyft highly values having employees working in-office to foster a collaborative work environment and company culture. This role will be in-office on a hybrid schedule — Team Members will be expected to work in the office at least 3 days per week, including on Mondays, Wednesdays, and Thursdays. Lyft considers working in the office at least 3 days per week to be an essential function of this hybrid role. Your recruiter can share more information about the various in-office perks Lyft offers. 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. Salary ranges are dependent on a variety of factors, including qualifications, experience and geographic location. Your recruiter can share more information about the salary range specific to your working location and other factors during the hiring process.
Lyft may use artificial intelligence to screen applicants, however, Lyft employees make the ultimate selection and hiring decisions.
This job fills an existing vacancy.
How we rate this
Data Engineer at Lyft rates 65 out of 100 for how much of the daily work is AI. That makes it Works on AI (AI Level 3 of 4). The level is about AI in the job, not seniority.
Works on AI. The daily work is on AI products, without building the model.
- ●●●● Builds AI80 to 100
- ●●●○ Works on AI60 to 79
- ●●○○ Uses AI40 to 59
- ●○○○ Little AI0 to 39
Levels come from how often the tools, models and workflows of the role are named in the posting itself. Read the description and count the AI tools, models and workflows it names.
Prepare for this job
Built from this posting and from similar jobs on Level.
Skills and AI tools this role asks for
Also common in data engineer jobs at this level
Pay
- This job starts at
- $108k
- Typical data engineer job
- $147k
This posting starts 26% below the typical data engineer job. See data engineer jobs
Questions you could be asked
- How do you decide when an AI agent can act on its own versus asking for approval first?
- Tell me about a project where data engineering was part of your work. What did you do?
- Tell me about a project where etl was part of your work. What did you do?
- Tell me about a project where data modeling was part of your work. What did you do?
- Tell me about a project where pipeline orchestration was part of your work. What did you do?
Adapt your resume
- List these exact terms on your resume: AI agents, Data Engineering, ETL, Data Modeling, and Pipeline Orchestration. An applicant tracking system matches the wording, not the idea.
- Attach one line of real, concrete experience to at least one of them. A tool named with nothing behind it rarely survives a human read.
- Show where AI is part of your daily process, not a one-off project. This role expects it to be a running habit.
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