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 Data Orchestration team within Data Platform is responsible for managing orchestration engines including Airflow and Flyte, which power and accelerate data pipelines and machine learning processes at the scale required by Lyft products. These components support a variety of use cases, including but not limited to Core Dataset, Financial Infra, Pricing, Estimated Time of Arrivals (ETA), and Mapping. The team's clusters host and serve thousands of workflows and over 100,000 executions on a daily basis.

　　As a Software Engineer, with your technical expertise you will manage project priorities, deadlines, and deliverables. You will design, develop, test, deploy, maintain, and enhance the platform offerings. Your work will have a major impact on several areas of the business.

　　We are looking for candidates who are self starters and have a proven track record of delivering software solutions that can solve critical business needs. The candidate should be able to dive deep into any problems with lots of ambiguity and build a technical solution to solve it. They should be willing to take ownership of a project or a feature and be able to drive it from design to implementation.

　　Responsibilities:

　　Design, develop, deploy, monitor, operate and maintain existing or new elements of our platform

　　Help establish roadmap and architecture based on technology and our needs

　　Write well-crafted, well-tested, readable, maintainable code

　　Analyze our internal systems and processes and locate areas for improvement/automation

　　Collaborate with product org stakeholders to address and prioritize custom edge cases

　　Help lead large projects from inception to positive execution

　　Unblock, support and communicate with internal partners to achieve results

　　Experience:

　　3+ years of software engineering industry experience and with data structures/algorithms

　　2+ years of experience building and developing large-scale infrastructure, distributed systems or networks, and/or experience with data infrastructure

　　Experience working with kubernetes and container technologies (e.g. Docker, cri-o, etc)

　　Familiar with a cloud-based environments such as AWS/GCP/Azure

　　Benefits:

　　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.

　　Starting in September 2023, 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 Area is $139,500 - $155,000. 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.