Senior Data Engineer

Hyperbolic Labs • San Francisco, CA

4d

About The Position

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.
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.

Requirements

• 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.

Nice To Haves

• 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.

Responsibilities

• Build our data infrastructure from 0 to 1.
• Take ownership of the data warehouse, the pipelines that feed it, and the tooling that keeps it healthy.
• Design data models for new business lines, figuring out what to model and how as new products (like spot and inference) come online.
• Ensure data reliability and quality through testing, documentation, and governance.
• Support production systems: monitoring, troubleshooting, and performance tuning.

What This Job Offers

• Job Type: Full-time
• Career Level: Senior
• Education Level: No Education Listed