Senior Data Engineer, Mapping

At Lyft, our purpose is to serve and connect. To do this, we start with our own community by creating an open, inclusive, and diverse organization.

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.

To strengthen our efforts, we are hiring a Senior Data Engineer helping us making 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.

We are looking for a Data Engineer to build a scalable data platform. You will proactively propose new ideas, evaluate multiple approaches and choose the best one based on fundamental qualities and supporting data. You will communicate highly technical problems working along with our cross-functional team and you will have ownership of our core data pipeline that powers mapping’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, 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:

• Owner of the core data pipelines in mapping, 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
• Participate in on-call rotations to ensure high availability and reliability of workflows and data
• 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. 
• 4+ 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 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 — 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. #Hybrid

The expected base pay range for this position in the Toronto area is $123,800-$172,000 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.