Data Engineer (Data Product)

We are looking for a Data Engineer with 2+ years of experience (this can also be a senior hire) to own complex consumer-data domains end-to-end and turn messy raw signals into trusted, production-ready data products. This is a unique role where your work output directly drives enterprise-grade revenue – GTM can immediately start selling what you build. You'll sit at the intersection of data engineering and applied data science, acting as the "interior designer" who fills the infrastructure built by the data platform team with high-value, productized data. The ideal candidate is a first-principles problem solver who lives and breathes data, thinks creatively about what datasets mean in the real world, and ships pipelines that power real products. Exceptional junior candidates from top programs (MIT, Stanford, Berkeley) with high slope are also encouraged to apply.

What you will be doing

- Investigating large, messy, and unfamiliar datasets – establishing their grain, relationships, coverage, and fitness for product use cases – then designing durable domain models and derived attributes from them

- Building and operating ingestion and transformation pipelines that bring your work into production, including validation, observability, and backfills

- Going on "data quests" – identifying and evaluating new data sources, determining how they improve the consumer graph, and finding clever ways to extract signal from imperfect inputs

- Becoming Minerva's internal expert on one or more data domains (e.g., identity graph, property data, consumer intent) – deeply understanding what is useful, what is misleading, and what to build next

- Partnering with data scientists, platform engineers, and customer-facing teams to turn ambiguous business questions into scalable, revenue-generating data products