You will be responsible for contributing to and helping guide the future of our systems that hold petabytes of data, serve millions of queries per second, and are used by hundreds of millions of Twitter users as they connect, explore, and interact with information and one another. You will develop highly-performant algorithms and data structures, solve complex distributed systems problems, and envision and innovate the next solutions that will bolster the foundation of Storage infrastructure.
Operating our own systems at hyper growth levels is a rewarding challenge, it is what helps make us great. We are a tight knit and passionate group that loves working together, and we are looking for exceptional additions to our flock. You will empower dozens of engineering teams, hundreds of co-workers, and millions of users to dream of new insights and new possibilities.
Observability Metrics Backend - We build the backend infrastructure for the highly critical metrics service handling ~10B metrics/minute with significant growth rate in scale. The infrastructure includes various metrics collection and ingestion frameworks, a highly optimized purpose-built time series database (MetricsDB) , a query engine to power a custom query language, indexing services and some massive hadoop pipelines. We are working on pushing the boundaries of this stack even further. More information about Twitter Observability stack can be found here and here.
You enjoy new challenges and are passionate about continually pushing the envelope of scale. You take satisfaction in building resilient, high-performance, and thoroughly tested systems that can power the most business-critical applications. You want to learn, work with, and contribute to cutting-edge open-source technologies.
The ideal candidate has experience with distributed storage systems such as Cassandra, HBase, BigTable, S3 or experience with container managers like Kubernetes and actively makes contributions to open-source software.
Twitter’s globally distributed, real-time communications network generates trillions of events and petabytes of data per day. To handle this scale, as engineers on the Storage Infrastructure team, we build world class distributed databases, caching, and messaging infrastructure