If you are passionate about building large-scale data processing systems and are motivated to make an impact through a next-generation, robust, and scalable data platform - we would love to talk to you. We use data to fuel all of Lyft’s decisions, so we need talented people like you to build and scale our data infrastructure to reliably deliver the timely insights that enable us to create a game-changing transportation marketplace.
Our Data team builds and supports infrastructure to ingest, curate, and serve the myriad real-time and periodic data demands of the business. If you're interested in being at the center of Lyft's efforts to deliver delightful experiences to all of our stakeholders, this might be the role for you.
You will report into an Engineering Manager.
- Design and own the roadmap and build-out of how interactive data queries are answered at Lyft
- Demonstrate customer-focused ownership of the core Presto infrastructure, taking the lead on building and scaling our infrastructure to adapt to rapid changes (almost always growth!) in the types and quantity of analysis demands from our customers
- Build large-scale, flexible, documented, and reliable distributed systems in a real-time, production environment serving billions of rides
- Operate our community-sourced tooling (including Presto, Druid, and Kubernetes) in a 24/7 environment while minimizing pager load and the need for manual intervention
- Write well-crafted, well-tested, readable, maintainable code
- Participate in code reviews to ensure code quality and distribute knowledge, including Open-Source projects
- Share your knowledge by giving brown bags, tech talks, and evangelizing appropriate tech and engineering best practices
- A typical successful candidate will have 7+ years of relevant professional experience, but even if you have less: apply anyway and prove us wrong!
- Experience in distributed data processing and analysis platforms; knowledge of Presto and/or Druid is especially prized
- Familiarity with the Big Data Ecosystem (MapReduce, Yarn, HDFS, Hive, Parquet, etc.) is a plus
- Demonstrated skill in working at scale; completed projects with Kubernetes (k8s), Envoy, Kafka, and/or AWS are a big plus
- Understanding of distributed systems concepts and principles (consistency and availability, liveness and safety, durability, reliability, fault-tolerance, consensus algorithms, etc.)
- Ability to map unknown systems onto known principles in order to generate actionable insights; if you have a copy of XKCD 2217 on your wall, chances are very good that you’re right for the job