At Lyft, our mission is to improve people’s lives with the world’s best transportation. To do this, we start with our own community by creating an open, inclusive, and diverse organization.

The Real Time Supply Management team at Lyft is responsible for managing our suite of real time driver earnings products, driving top business goals around financial metrics and marketplace performance. The team develops and improves algorithms to automate the management of our real time earnings products, develops new earnings products, and manages financial performance of these products to manage the growth of the business. 

As a Data Engineer at Lyft, you will be a part of an early stage team that builds the data transport, collection, and storage, and exposes services that make data a first-class citizen at Lyft. We are looking for a Data Engineer to build a scalable data platform. You’ll have ownership of our core data pipeline that powers Lyft’s top line metrics; You will also use data expertise to help evolve data models in several components of the data stack; You will help architect, building, and launching 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, Marketplace and many others.

Responsibilities:

• Work across teams to gather requirements and drive alignment on project goals
• Provide technical leadership to the team for executing projects within scope, time & quality constraints
• Evangelize best practices within the team through tech talks, demos etc
• Take initiative and craft projects to improve customer experience & satisfaction by resolving long standing problems or by building important user facing features
• Owner of the core organization 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
• Unblock, support and communicate with internal & external partners to achieve results

Experience:

• 10+ years of relevant professional experience
• Experience with Hadoop (or similar) Ecosystem (MapReduce, Yarn, HDFS, Hive, Spark, Presto, Pig, HBase, Parquet)
• Strong skills in a scripting language (Python, Ruby, Bash)
• Good understanding of SQL Engine and able to conduct advanced performance tuning
• Proficient in at least one of the SQL languages (MySQL, PostgreSQL, SqlServer, Oracle)
• 3+ years of experience with workflow management tools (Airflow, Oozie, Azkaban, UC4)
• Comfortable working directly with data analytics to bridge Lyft’s business goals with data engineering

Benefits:

• Extended health and dental coverage options, along with life insurance and disability benefits
• Mental health benefits
• Family building benefits
• Access to a Health Care Savings Account
• In addition to provincial observed holidays, team members get 15 days paid time off, with an additional day for each year of service 
• 4 Floating Holidays each calendar year prorated based off of date of hire
• 10 paid sick days per year regardless of province
• 18 weeks of paid parental leave. Biological, adoptive, and foster parents are all eligible

Lyft proudly pursues and hires a diverse workforce. 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 now if you wish to make such a request.

This role will be in-office on a hybrid schedule following the establishment of a Lyft office in Toronto — Team Members will be expected to work in the office 3 days per week on Mondays, Thursdays and a team-specific third day. Additionally, hybrid roles have the flexibility to work from anywhere for up to 4 weeks per year.