Hyperbolic
Senior Data Engineer
- Location
- San Francisco, CA, US
- Arrangement
- Hybrid
- Employment type
- Full-time
- Level
- Senior
- Posted
- 5 October 2026 (about a month ago)
Checked 9 days agoApplications go to the employer, never to RoleSprint
About this role
WHO WE ARE
Join us in putting the world’s compute behind the people building what comes next.
At Hyperbolic, we’re making global AI compute liquid. We bring fragmented, heterogeneous GPU capacity together into one unified, productive platform, making it easier to access, sell, resell, manage, and orchestrate the resources that power AI. For neocloud, we turn GPU capacity into productive infrastructure that delivers lasting value and accelerate their time to market.
We believe bold ideas deserve the computing power to become reality. We’re building toward a future where compute flows as freely as electricity, available when and where it’s needed, so builders everywhere can turn their most ambitious ideas into breakthroughs.
We’re looking for curious, driven people who take ownership, challenge assumptions, and care deeply about what they build. If you’re energized by hard problems and want to help shape how the world accesses AI, we’d love to build with you.
ABOUT THE ROLE
This is Hyperbolic's first dedicated Data Engineer, and you will build our data infrastructure from 0 to 1. You'll be one half of a two-person data team, working alongside our data analyst, which means a high degree of autonomy and a direct line to impact. Today our product engineers maintain the data stack on top of their day jobs. You will take ownership of the data warehouse, the pipelines that feed it, and the tooling that keeps it healthy.
The timing matters. As we launch new products like inference, our data volume will grow fast, we will add more data sources, and more teams will rely on BI and reporting. Scrappy processes and off-the-shelf tools won't keep up at that scale, and you will build what comes next.
You will sit between our data analysts and engineering, partnering with both to make sure the right data is reliable, fast, and cost-efficient to use.
Our current data stack includes Redshift, Postgres, and Hex, with Polytomic for ingestion.
WHO YOU ARE
- Track record of independently building and maintaining a data warehouse that ingests and aggregates data from multiple sources using industry-standard tooling
- Experience designing data models for new business lines, figuring out what to model and how as new products (like spot and inference) come online
- Experience ensuring data reliability and quality through testing, documentation, and governance
- Familiarity with data lakes and data warehouses, and when to use each
- Deep knowledge of Postgres, including partitioning, data archival, and moving large datasets
- Experience working with large datasets
- Experience supporting production systems: monitoring, troubleshooting, and performance tuning
- Strong communication skills, with the judgment to push back on requests that would add tech debt and explain why
PREFERRED QUALIFICATIONS
- Familiarity with the AWS ecosystem (this can be learned on the job)
- DBA experience
- Experience setting up CI/CD for data pipelines
- Background in GPU infrastructure, cloud computing, or AI infrastructure
- Experience at an early-stage, high-growth technical company
Hyperbolic is an equal opportunity employer. We celebrate diversity and are committed to creating an inclusive environment for all employees.
Work location
- San Francisco, CA, US
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About this listing
Published on Ashby under the board identifier Hyperbolic, which is the name the employer’s own job board carries. RoleSprint has not verified the company’s registered or trading name, so it is shown exactly as published rather than tidied up.
RoleSprint is not the employer and not a recruiter. Applications are made on the employer’s own site and never reach us; what RoleSprint does is help you decide whether a role is worth your time and prepare for it if it is.
Published 5 October 2026, last checked 9 days ago. A posting stops being advertised here 90 days after the employer published it, and one the employer takes down is marked closed rather than quietly removed.