Mixpanel is an event analytics platform for builders who need answers from their data at their fingertips—no SQL required. When everyone in the organization can see and learn from the impact of their work on product, marketing, and company revenue metrics, they are poised to make better decisions. Over 9,000 paid customers, including companies like Netflix, Pinterest, Sweetgreen, and Samsara, use Mixpanel to understand their customers and measure progress. Our commitment is to provide the most comprehensive and reliable analytics platform accessible and trusted by all. We are actively recruiting for multiple Software Engineers across different levels for our org! About the Role Mixpanel is powered by a custom distributed database. This system ingests more than 1 Trillion user-generated events every month while ensuring end-to-end latencies of under a minute and queries typically scan more than 1 Quadrillion events over the span of a month. Over the last year, our inbound traffic has doubled. As our existing customers grow in volume and we add new ones, we expect this growth in traffic to continue. The Distributed Systems engineering teams are responsible for adding new capabilities and ensuring the smooth operation of the underlying systems. A typical project requires a thorough understanding of how not just your service works but also how it interacts with other components. Here are some projects we've worked on in the past to give you an idea of what to expect. Most of the systems in our stack provide at least once semantics. As a result, we risk duplicating events that flow through them. To overcome this limitation, we added support for event deduplication that can work at our scale. Typical approaches for deduplication don't perform well on large amounts of data, so we had to do something highly custom for our stack. We wrote about this on our engineering blog here. Back in 2019, we migrated our ingestion API service from Python to Golang for better performance and type safety. We had to do this while ensuring that both systems handle data the same way. Because we had to compare, both, HTTP responses and transformed payloads, nothing out of the box worked for us. This blog post talks about how we did the actual migration without any customer visible downtime. In 2021, as our traffic grew almost 100%, the cost of storing data became untenable. Our engineers worked on an incremental way to eventually realize almost $30000 in savings per month. If projects like the ones listed above excite you, the Distributed Systems engineering team will be a great fit.
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Job Type
Full-time
Career Level
Mid Level
Education Level
No Education Listed
Number of Employees
251-500 employees