# Data Engineer, Data Products at Minerva

- Company: Minerva
- What the company does: An AI native financial institution. We're making financial services fast and affordable for all, starting with accounting. Backed by Y Combinator.
- Company website: https://joinminerva.ai
- Type: Startups (AI role)
- Level: Mid level
- Location: New York City
- Work setup: On-site
- Pay: $200K to $225K base salary per year (USD)
- Posted: 2026-08-06
- Apply by: 2026-10-08
- Apply: https://jobs.ashbyhq.com/minerva/dbfa0d14-3fdb-432d-bc03-c0364e313a39
- Page: https://www.1752.vc/careers/jobs/minerva-data-engineer-data-products/

## About the role

Minerva's data is not just infrastructure beneath our product; it is also one of our products. We are looking for a Data Engineer who can take ownership of complex consumer-data domains, develop a deep understanding of how their datasets relate and turn messy raw signals into trusted attributes and production data products. This role & Minerva are quite unique in the sense that GTM can immediately start selling your work output and generate enterprise-grade revenue in a matter of weeks.

## What they're looking for

- - 2-5+ years working as a data engineer, software engineer or applied data scientist in a data-heavy context. Your prior title matters less than evidence that you live and breathe data
- - Highly proficient in Python and SQL
- - Driven by first-principles thinking. You can take an ambiguous data problem, determine what must be true, interrogate the available evidence and design a practical path to an answer
- - Strong intuition for data cleaning, ingestion and data modeling. We expect these foundations to be second nature so your thinking is free for larger and more ambiguous data initiatives, especially given the leverage of modern AI coding tools
- - Comfortable building and deploying production data pipelines, not just analyzing data in notebooks or handing specifications to another engineering team
- - Able to balance analytical depth with engineering pragmatism: you care whether an attribute is conceptually valid and whether it can be produced reliably at scale, you know when a new idea won't provide any lift

Tags: Engineering