Data Engineer, Driver Team at Lyft, Inc.

Toronto, Ontario, Canada -

Full Time

Start Date

Immediate

Expiry Date

22 Dec, 25

Salary

135000.0

Posted On

23 Sep, 25

Experience

2 year(s) or above

Remote Job

Yes

Telecommute

Yes

Sponsor Visa

Skills

Data Engineering, Data Pipelines, Spark, Python, SQL, AWS, Hadoop, S3, Hive, Presto, Airflow, ETL Processes, Data Warehousing, Collaboration, Data Quality, Schema Design

Industry

Ground Passenger Transportation

Description

Applications for this position will be accepted until October 6, 2025. Lyft reserves the right to close the application process early or extend the deadline at its discretion. 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. Our transport network serves the needs of millions of people every day who want to get from one place to another using Lyft cars, bikes and scooters, with public transportation, or on foot in the most efficient way. To serve these needs, we need to suggest the fastest, most affordable and safest routes. We achieve this by processing millions of rides, taking into account the latest traffic information and analyzing the preferences of drivers.The Driver team sits at the heart of this mission, creating tools and insights that power safe, efficient, and rewarding driver experiences. To strengthen our efforts, we are hiring a Data Engineer to help us make data driven decisions. Data Engineering is at the heart of Lyft’s products and decision-making. As a Data Engineer at Lyft, you will be tasked with developing robust data infrastructure—encompassing data transport, collection, and storage—and providing services that enable our leadership to make informed, risk-reducing decisions. You will help architect, build, and launch scalable data pipelines to support Lyft’s growing data processing and analytics needs. 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. Our technology stack is based on the latest technologies such as AWS, Kubernetes and Apache Airflow. You will work with incredibly passionate and talented colleagues from software engineering, machine learning and data science on projects that delight millions of passengers and drivers. Responsibilities: Build and maintain reliable, scalable data pipelines supporting driver insights and trip routing Improve data models and schema design to meet evolving engineering and business needs Monitor and improve data quality, consistency, and performance Support internal users with self-serve ETL tools and real-time analytics pipelines Collaborate cross-functionally with product, engineering, and data science teams Experience: Bachelor's degree in Computer Science, Engineering, Mathematics, Statistics, or a related field 2+ years of 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 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 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 $108,000 - $135,000 CAD. Salary ranges are dependent on a variety of factors, including qualifications, experience and geographic location. Range is not inclusive of potential equity offering, bonus or benefits. Your recruiter can share more information about the salary range specific to your working location and other factors during the hiring process.

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Responsibilities

Build and maintain reliable, scalable data pipelines supporting driver insights and trip routing. Improve data models and schema design to meet evolving engineering and business needs.