Fluency is looking for a next-level data engineer to build the data infrastructure that ontologizes how work happens across Fortune 500 organizations.
You'll be working on problems that have no established solutions. We're processing terabytes of workflow data per enterprise customer in real-time – systems that map, relationship, contextualize, and analyze work patterns across entire orgs. Think human genome project, but for enterprise workflows.
You'll invent new data primitives and paradigms. This means designing novel data structures for representing work, building pipelines that process billions of events per day, and writing whitepapers on approaches that don't exist yet.
You're operating at the bleeding edge of data science where the playbook hasn't been written.
We're backed by T1 VCs like Accel and are hitting an inflection point with Enterprises all around the globe.
You'll work directly with founders and our engineering team. The technical challenges are unprecedented: real-time processing at massive scale, creating a universal taxonomy for work across every industry, and building systems that can handle the most complex enterprise data environments on earth.
If you don't have a CS background, you're challenged to beat one of the founders in a 1:1 whiteboard duel on DS&A judged by Hung. Neither founders have formal CS background, but come prepped.
There will be an expectation to stay up to business context, which could involve:
We work with some of the world's largest:
You're expected to be in love with the craft. You're expected to like laughing. You're expected to want to work on novel problems. You're expected to find satisfaction in novelty. You're expected to solve under obscurity.
Full-time, in-person role based in San Francisco, CA.
We strongly encourage applicants from underrepresented backgrounds to apply. Diverse teams build better products — see value #5.