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.
If you are passionate about building large-scale data processing systems and are motivated to make an impact in creating a robust and scalable data platform - we would love to talk to you. Data is the only way we make decisions, it’s the core of our business helping us create an exceptional transportation experience for our customers and providing insights into the effectiveness of our product & features.
You will be a part of an early team that builds the data transport, collection, and storage, and exposes services that make data a first-class citizen at Lyft. You will help shape the vision and architecture of Lyft’s next-generation data infrastructure, making it easy for developers to build data-driven products and features connecting millions of our drivers and passengers. You will be responsible for developing a reliable infrastructure that scales with the company’s incredible growth. Your efforts will allow access to business and user behavior insights, leveraging huge amounts of Lyft data to fuel several teams such as Analytics, Data Science, Marketplace, Fraud and many others.
We are a set of engineers constantly striving to create an amazing experience for our customers and ourselves, and we believe data brings everything together. We build and operate the platform used by the rest of the company for stream and batch computation serving mechanisms to train ML models. You will be a part of an experienced engineering team and work with passionate leaders on challenging distributed systems problems. We regard culture and trust highly and believe you will add positively to it in your own way.
Build and operate large-scale data infrastructure programs (performance, reliability, monitoring)
Experience working with and building real-time compute and streaming infrastructure - Kafka, Kinesis, Flink, Storm, Beam
Experience configuring, identifying performance bottlenecks and tuning MPP databases
Able to think through long-term impacts of key design decisions and handling failure scenarios
Experience with workflow management (Airflow, Oozie, Azkaban, UC4)
Lyft is an Equal Employment Opportunity employer that proudly pursues and hires a diverse workforce. Lyft does not make hiring or employment decisions on the basis of race, color, religion or religious belief, ethnic or national origin, nationality, sex, gender, gender identity, sexual orientation, disability, age, military or veteran status, or any other basis protected by applicable local, state, or federal laws or prohibited by Company policy. Lyft also strives for a healthy and safe workplace and strictly prohibits harassment of any kind. Pursuant to the San Francisco Fair Chance Ordinance and other similar state laws and local ordinances, and its internal policy, Lyft will also consider for employment qualified applicants with arrest and conviction records.