At Cube Dev, we are building a technology stack for modern analytics and our mission is to make it accessible to developers around the world.
We are focused on bottom-up adoption, and most of our software is open-source. Cube, our flagship open-source product, has over 10,000 stars on GitHub and over 3,000 community members in Slack. It powers companies ranging from Apple, Intel, and Walmart to small Silicon Valley startups.
We are a 15-person remote-first team distributed over the US, UK, and Eastern Europe with an HQ in San Francisco, funded by top-tier Silicon Valley venture funds that have previously invested in Redis, Hazelcast, Gradle, and other infrastructure software startups.
Cube is used to build analytical APIs over trillion data point datasets in SQL databases (e.g., Postgres, ClickHouse) and data warehouses (e.g., Google BigQuery, AWS Athena, Snowflake). Such APIs serve requests with sub-second latency and high concurrency thanks to Cube Store, our performant open-source distributed columnar storage written in Rust and based on Apache Arrow and DataFusion.
We're determined to further enhance Cube's performance and support advanced workloads. That's why we're looking for a distributed systems engineer to join our Cube Dev team to evolve Cube Store.
During the first months, you'll be working on fine-tuning Cube Store's performance, improving its architecture, and supporting Kafka integration for data streaming.
This is a remote position. Any location is okay as long as we can expect you to be online till 1 pm PT. We can pay for your desk at the co-working space that you choose to work from. Down the road, we offer an optional relocation to our HQ in San Francisco, California with visa (H1-B or O-1) sponsorship. Also, we offer stock options in our US company.