About NerveStax
NerveStax builds AI agents for data teams. They work on the stack a team already runs: dbt, Airflow, the warehouse and git. The agents load data, change models, look after schedules and investigate pipeline alerts.
Every change is tested in a sandbox and reaches a person as a pull request to approve. We are an early, small team in private beta, onboarding data teams now, hosted or self-hosted.
About the role
Agents are only as good as what they know about a platform. You'll build that knowledge and the integrations behind it: turning a project's artifacts into a record of assets, jobs and runs; testing changes in the team's own orchestrator; and loading data from their sources. We start where most data teams are, with dbt and Airflow, and the surface keeps widening: more sources, more warehouses, more of the tools teams already run.
What you’ll do
- Build the record of a customer's platform — assets, jobs, runs, lineage, freshness — and keep it accurate as their tools change.
- Extend the harness that tests a pull request's changes in the team's own orchestrator, and add the next orchestrators.
- Grow ingestion from its first sources towards the long tail of databases, APIs and files that teams actually load.
- Add warehouses and keep behaviour consistent across them, including the ones we haven't supported yet.
- Detect drift and schema changes, and make them visible to agents and to people.
- Work through real projects and pipelines with the teams using NerveStax, including the unusual ones.
We’re looking for people who
- Have run data transformation and orchestration in production and know where they break.
- Know at least one warehouse well, and are curious about how the others differ.
- Write clear Python and SQL, and test what you write.
- Care more about data being correct than about a pipeline turning green.
- Can explain data engineering trade-offs to engineers who don't do it every day.
- Like building integrations that keep working as the tools underneath them change.
Nice to have
- Worked with metadata standards or artifacts such as OpenLineage or dbt.
- Built or maintained connectors, a dbt adapter or an Airflow provider.
- Used the GitHub or GitLab APIs in production.
What we provide
- Competitive salary and meaningful equity.
- Ownership of real problems, from design to production.
- Direct work with the data teams who use the product.
- Your choice of tools, including AI coding agents.
- A say in what the product and the company become.
How to apply
Email us. There is no form, and you don't need a cover letter. Send it to [email protected] with the subject “Founding Engineer, Data Platform”, and include:
- A few lines about you and why this role.
- Links to work you're proud of: code, writing, talks or a product you shipped.
- Where you are based and when you could start.
We read every email and reply. What happens next ›