Software Engineer, Distributed Systems (Core) – Remote (US/Canada)

$180k -$320k

We are looking for a distributed systems engineer to work on the systems that power the syncing engine our customers and other engineering teams rely on. This presents an exciting challenge where you can apply your expertise in distributed systems, performance optimization, and troubleshooting to push the boundaries of what is possible and meaningfully improve our ability to move massive amounts of customer data. This role also offers a unique opportunity to work on a multi-cloud, multi-region infrastructure that supports a global customer base. You will own and deliver projects from start to finish; work directly with customers to solve their hardest scaling problems; and have significant influence over what we work on as a team and company.

Requirements

• 7+ years of experience as a software engineer with a very high level of general aptitude and experience working in distributed systems
• Strong backend engineers (not full stack), please send them to our senior full stack role instead.
• An engineer passionate about solving hard technical problems that generate real value for customers.
• You've created event collection or data streaming services that power company-critical systems ( work with message queues,​ Kafka,​ SQL databases,​ Kubernetes,​ Docker)
• You've owned systems that have undergone orders of magnitude of growth and helped them scale accordingly
• Experience and comfort with distributed systems and high-scale systems, or the ability and desire to build this experience quickly. You have built syncing engines that process and move terabytes of data per day in a scalable way
• Created event collection or data streaming services that power company critical systems
• Owned systems that have undergone orders of magnitude growth and helped them scale accordingly
• You have relevant skills and are a fast learner who is excited to take on the challenges we face

Some of the problems we'll be working on include:

• Sync Speed: Customers want to sync a lot of data to important destinations like Facebook and Snapchat, which requires us to analyze every part of our syncing process and find where we can optimize to sync data more quickly
• Streaming Syncing: We currently sync data from sources in batch only, but envision a world where we also do syncs in real-time and support streaming sources like webhooks and queues
• Scalability and Reliability: As part of our rapid growth, we're always evaluating current and future bottlenecks in scaling and reliability, and architecting for the next order of magnitude of growth
• Personalization API: Our Personalization API product provides a low-latency caching layer on top of data warehouses that enables customers to use their data warehouse for real-time personalization use cases with <30ms p90 response times with QPS in the millions

Education

• Graduated from a top 30 CS program such as:​ University of Waterloo,​ Harvard,​ Columbia,​ Princeton,​ Stanford,​ UC Berkeley,​ MIT,​ CMU,​ Caltech,​ Cornell,​ Duke,​ Dartmouth,​ Brown,​ IITs