Jobs Companies Lyft Data Engineer, Pricing

Sobre esta vaga de Data Engineer, Pricing na Lyft

Lyft · Híbrido · Toronto, Canada

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.

Pricing is at the core of Lyft’s business, driving revenue, balancing supply and demand, and shaping user experience through real-time and strategic decisions. The Pricing team builds and maintains the systems that determine what a ride should cost—incorporating demand forecasts, marketplace signals, promotions, cost models, and more.

As a Data Engineer on the Pricing team, you will help build the data foundation that powers Lyft’s pricing strategies. You will architect, build, and maintain scalable data pipelines to support real-time pricing, experimentation, analytics, and modeling. Your work will enable integration with partner teams and allow stakeholders across Engineering, Data Science, and Product to make data-informed decisions that directly impact Lyft’s growth and profitability.

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 directly impact millions of riders and drivers.

Responsibilities:

  • Owner of the pricing 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
  • Unblock, support and communicate with internal & external partners to achieve results

Experience:

  • Bachelor's degree in Computer Science, Engineering, Mathematics, Statistics, or a related field. 
  • 2+ years of relevant professional experience
  • Strong experience with Spark
  • Experience with Hadoop (or similar) Ecosystem, S3, DynamoDB, 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)
  • Experience with workflow management tools (Airflow, Oozie, Azkaban, UC4)
  • Comfortable working directly with data and business partners 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
  • 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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Como este salário de Data Engineer se compara

Esta vaga paga $108,000/yrabaixo da faixa típica para vagas de Data Engineer.

$106,200 a mediana $159,500 $209,033

Faixa típica $118,618–$199,500/yr, com base em 15 vagas de Data Engineer comparáveis na JobsRadar (pagamento anualizado em USD). Ver insights salariais de Data Engineer →

Sobre a Lyft

Wherever you’re headed, count on Lyft for rides in minutes. The Lyft app matches you with local drivers at the tap of a button. Just request and go. Ride by ride, we’re changing the way our world works. We imagine a world where cities feel small again. Where transportation and tech bring people together, instead of apart. We see the future as community-driven — and it starts with you.

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