Software Engineer, Data Platform

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.

The Data Trust team within Data Platform is responsible for empowering Lyft with reliable and easily discoverable data, while fostering proactive data stewardship, and streamlining data operations, to drive informed decision-making and foster innovation.  The team owns components including Verity as data quality tooling, Amundsen as data discovery tooling and data governance. 

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.

• →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

• 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