Senior Data Engineer
Hyperbolic
San Francisco, CA · Posted November 6, 2026
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Where San Francisco, CA placed in our monthly rankings, month by month. Each month stays online at its own address.
November 2026
- #1Best cities for security jobs316 openings · of 20
- #1Best cities for technology jobs7,178 openings · of 100
- #1Best cities for financial services pay after cost of living$173k · of 33
- #1Best cities for entry-level jobs that want AI skills35% · of 100
- #1Best cities for entry-level jobs that want AI skills in the West Coast35% · of 54
- #1Cities with the most jobs that do not need a four-year degree in the West Coast902 jobs · of 47
Rankings about data & analytics jobs
- Best cities for data and analytics jobs #1 New York (1,713 openings)
- Best cities for data and analytics pay after cost of living #1 Foster ($232k)
- Most requested AI skills in data and analytics jobs #1 Machine learning engineering (17.1%)
- AI tools named most often in data and analytics jobs #1 Databricks (7.6%)
- Employers with the most data and analytics jobs #1 Amazon (711 roles)
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Pay compared with the market
This listing does not state pay. Across 30 open senior data engineer listings that state pay, the middle half runs $137,500 to $190,000 and the median is $163,000.
Listed pay is what employers advertise, not what people are paid.
How AI is used in this kind of work
Among database architects, AI is already used for a large share of the tasks. Measured exposure for database architects: 58% (high).
Share of this job’s tasks that AI is already used for at work, from real usage. It is not a forecast of job loss, and a low number means no use seen yet. Source: Anthropic Economic Index.
Skills this job asks for
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About the job
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.