招聘
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 Map Reduce 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.
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关于Lyft

Lyft
PublicLyft, Inc. is an American company offering ride-hailing services, motorized scooters, and bicycle-sharing systems in the United States and Canada, and, via its Free Now mobile app, Europe. Lyft is the second-largest ridesharing company in the United States after Uber.
1,001-5,000
员工数
San Francisco
总部位置
$3.2B
企业估值
评价
3.9
10条评价
工作生活平衡
3.8
薪酬
3.2
企业文化
4.2
职业发展
3.5
管理层
3.7
72%
推荐给朋友
优点
Flexible hours/schedule
Great team culture
Good work-life balance
缺点
Long hours
Fast-paced work environment
Pay could be better
薪资范围
41个数据点
Junior/L3
Mid/L4
Senior/L5
Junior/L3 · Analyst
1份报告
$146,004
年薪总额
基本工资
$126,960
股票
-
奖金
-
$146,004
$146,004
面试经验
2次面试
难度
3.0
/ 5
时长
14-28周
录用率
50%
面试流程
1
Application Review
2
Recruiter Screen
3
Technical Assessment
4
Technical Interview
5
Onsite/Virtual Interviews
6
Offer
常见问题
Coding/Algorithm
System Design
Behavioral/STAR
Technical Knowledge
新闻动态
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2d ago
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3d ago
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