An AI native financial institution. We're making financial services fast and affordable for all, starting with accounting. Backed by Y Combinator.
About the role
Every new data source starts as someone else's problem: an API with rate limits, a vendor file that arrives late and gets corrected twice, a schema that changes without warning. Today, adding a new vendor feed still takes hand-built work. Found on 1752vc Careers, the job board for startup and VC roles.
What they're looking for
- Typically three or more years building and supporting production data pipelines, or equivalent ownership
- You've brought in data from many vendors and source types, including messy data at scale, and kept it running after launch
- Practical judgment about incremental processing, backfills, failures and cost. You can show the data stayed correct as volume grew
- You've automated repeated work or built components other engineers actually used
- Strong Python and SQL
- You pin down what a source owner actually needs, and you write down what you will and won't support
More about this role
Minerva builds AI for marketing leaders. We work together with marketers to automate and accelerate their workflows with AI agents. Our agents augment the end-to-end workflow of the marketer by automating analysis, campaign planning, activation, measurement and reporting.
Customers like the NBA, Ramp, Wander, Hard Rock Stadium Group and Luxury Presence use Minerva to develop a better understanding of their customers and introduce AI specifically built to understand the customer into their commercial organizations. Our campaigns outperform other tools because we built the entire stack: from identity to enrichment to data integration as well as agents to action and report on the analysis.
We've raised $20M from The General Partnership, 8VC, Lingotto, NBA Investments, Topology Ventures, Future Positive, Background Capital and many others. Our team brings together operators and investors from Citadel, Dentsu, Bridgewater, Meta Superintelligence, Growthloop, Amazon and Lazard, alongside engineers and researchers from Berkeley, MIT, Stanford and Cambridge.
Every new data source starts as someone else's problem: an API with rate limits, a vendor file that arrives late and gets corrected...
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