Backend Engineer, Data

Minerva•New York, NY

1d•$150,000 - $236,000•Onsite

About The Position

Minerva is hiring an individual-contributor or senior individual-contributor Backend Engineer, Data on its product engineering team. The role makes first-party consumer data, brand models, and data-science scores usable in the product. You will work day to day with data engineering and data science; the Staff Data Engineer owns the golden model and publishes the semantic views used by this role. You will build product systems that let marketers sort, filter, and chart first-party data without live warehouse queries; surface propensity, LTV, churn, and product-fit scores; keep dynamic segments current; and translate plain-English questions into queries against a brand’s data. The position also owns the product side of data synchronization, extends data pipelines when needed, and ships features end to end across backend, schema, and app layers. The stack includes TypeScript, TanStack Start, React 19, Tailwind, Base UI, Vite, Bun, Zero, Postgres, Drizzle, Mastra, Temporal, Python, AWS Lambda, and Snowflake. The position is based in person at Minerva’s Williamsburg, Brooklyn office. Candidates must be authorized to work in the United States; visa sponsorship is considered case by case.

Requirements

Production experience with a cloud data warehouse; Snowflake is preferred.
Production TypeScript experience.
Experience shipping backend services on AWS, using Lambda or a similar service.
Current knowledge of AI tooling and changes in the latest releases of packages used.
Has built things independently and can demonstrate them.
Located in New York City or willing to relocate.
Authorized to work in the United States; visa sponsorship is considered case by case.

Nice To Haves

Experience with a sync engine such as Zero, Replicache, or ElectricSQL; the posting says this would be especially impressive.
Experience as a full-stack engineer at a data-heavy SaaS company who has owned the warehouse.
Experience as a product engineer at a warehouse-native analytics or activation company, making Snowflake feel fast inside an app.
Experience as a backend engineer who has shipped on a sync engine and wants to work with a large dataset.
Experience as a data engineer interested in owning the product feature that uses the data.

Responsibilities

Own the performance of first-party data in the app, deciding what to precompute, where it lives, and how it stays fresh so fields can be sorted, filtered, and charted without live warehouse queries.
Deliver model scores—including propensity, LTV, churn, and product-fit scores—on person, segment, and product pages, with full distributions rather than only a single number.
Build and maintain dynamic segments that update as new data arrives, with statistics ready for activation.
Own the in-app agent’s query tool, using semantic views published by the data platform team to translate marketers’ questions into the correct rows.
Own the product side of synchronization, including what is precomputed and the path from Postgres to the synced client.
Extend data pipelines by writing models or pipeline steps when a feature needs a table that does not yet exist.
Ship features end to end across components such as Python Lambdas, Zero schema changes, and TanStack Start pages.