Skills

Full description

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

Experience supporting production systems: monitoring, troubleshooting, and performance tuning
Track record of independently building and maintaining a data warehouse that ingests and aggregates data from multiple sources using industry-standard tooling
Experience working with large datasets
Strong communication skills, with the judgment to push back on requests that would add tech debt and explain why
Experience designing data models for new business lines, figuring out what to model and how as new products (like spot and inference) come online
Deep knowledge of Postgres, including partitioning, data archival, and moving large datasets
Experience ensuring data reliability and quality through testing, documentation, and governance
Familiarity with data lakes and data warehouses, and when to use each
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

Senior Data Engineer

Compensation

Not disclosed

Location

San Francisco, United States

Work setup

Not specified

Seniority

Senior

Employment

Not specified

Experience

Not specified

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

Experience supporting production systems: monitoring, troubleshooting, and performance tuning
Track record of independently building and maintaining a data warehouse that ingests and aggregates data from multiple sources using industry-standard tooling
Experience working with large datasets
Strong communication skills, with the judgment to push back on requests that would add tech debt and explain why
Experience designing data models for new business lines, figuring out what to model and how as new products (like spot and inference) come online
Deep knowledge of Postgres, including partitioning, data archival, and moving large datasets
Experience ensuring data reliability and quality through testing, documentation, and governance
Familiarity with data lakes and data warehouses, and when to use each
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