This is a core backend software engineering role (70% SWE / 30% Data) within our Mapping organization. You will focus primarily on building high-throughput services, distributed system architecture, and APIs, while leveraging large-scale spatial data to power Lyft's routing and mapping products.
Note: This position focuses on backend service architecture and platform scalability rather than traditional ETL, BI, or data modeling pipelines.
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.
As a Senior Software Engineer, Data on the Mapping team, you will collaborate with our world-class team of engineers, product managers, and scientists to grow and improve the quality of recommended routes and accuracy of our travel time estimations. You will lead the architecture and long-term technical direction of our offline experimentation tooling and route simulation services — the systems that let Lyft test routing changes safely before they reach production. You'll also build scalable data pipelines for experimentation, analytics, and machine learning models, along with the data governance and observability systems that keep them trustworthy. Your work will enable integration with partner teams and allow stakeholders across Engineering, Data Science, and Product to make data-informed decisions that directly impact Lyft’s growth and profitability.
Our technology stack is based on the latest technologies such as AWS, Databricks, Kubernetes and Airflow. You will work with incredibly passionate and talented colleagues from software engineering, machine learning and data science on projects that directly impact millions of riders and drivers.
Responsibilities
- Own core data pipelines end-to-end, building deep subject matter expertise in the systems you manage and defining/managing SLAs for pipelines, services, and datasets to ensure reliability at scale
- Serve as the technical owner and architectural lead for our offline experimentation platform and route simulation services, setting technical direction, evaluating trade-offs, and ensuring the systems scale with Lyft's routing and mapping ambitions
- Continuously evolve data models and schemas to meet business and engineering requirements
- Develop AI tools that support self-service management of data pipelines (ETL) and schema evolution, and perform hands-on SQL tuning to optimize data processing performance
- Write clean, well-tested, and maintainable code, prioritizing scalability and cost efficiency
- Participate in code and architecture reviews to ensure code quality and distribute knowledge
