At Lyft, community is what we are and it’s what we do. It’s what makes us different. To create the best ride for all, we start in our own community by creating an open, inclusive, and diverse organization where all team members are recognized for what they bring.

Here at Lyft, Data is the only way we make decisions. It is the core of our business, helping us create a transportation experience for our customers, and providing insights into the effectiveness of our product launch & features.

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.

• Owner of the core company 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

• 5+ years of relevant professional experience
• Strong experience with Spark
• 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)
• 1+ 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

• Great medical, dental, and vision insurance options
• Mental health benefits
• Family building benefits
• In addition to 12 observed holidays, salaried team members have unlimited paid time off, hourly team members have 15 days paid time off
• 401(k) plan to help save for your future
• 18 weeks of paid parental leave. Biological, adoptive, and foster parents are all eligible
• Pre-tax commuter benefits
• Lyft Pink - Lyft team members get an exclusive opportunity to test new benefits of our Ridership Program

Lyft is an equal opportunity/affirmative action employer committed to an inclusive and diverse workplace. All qualified applicants will receive consideration for employment without regards to race, color, religion, sex, sexual orientation, gender identity, national origin, disability status, protected veteran status or any other basis prohibited by law. We also consider qualified applicants with criminal histories consistent with applicable federal, state and local law.  

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.

The expected range of pay for this position in the San Francisco Bay Area is $162,000 - $180,000. 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.