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Solutions Architect

Job in New York, New York County, New York, 10261, USA
Listing for: Minerva
Full Time position
Listed on 2026-10-26
Job specializations:
  • IT/Tech
    Data Engineering, Data Analyst
Salary/Wage Range or Industry Benchmark: 192000 - 215000 USD Yearly USD 192000.00 215000.00 YEAR
Job Description & How to Apply Below
ABOUT MINERVA

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.

HOW WE DEPLOY
  • Every enterprise account moves from a data test to a pilot to production. The technical win usually decides the deal.

  • Each account has a team. The account executive owns the deal. A forward deployed marketer owns the pilot's outcome. A solutions architect runs the technical evaluation and standard onboarding. A forward deployed engineer takes the accounts that need custom work.

THE ROLE

Every deal reaches the moment when the buyer's data team asks how it actually works. Every new customer reaches the moment their data has to land in Minerva and come out scored. Today our founders and data leads handle both, and they sit on the critical path of every deal.

You take both moments. You run the demo and the technical evaluation, then you run the onboarding: data in, scoring live, the customer's team trained on the platform. Most of our enterprise customers come through you. The few that need custom pipelines or models go to our forward deployed engineers, and you know when to hand one off.

WHAT YOU'LL DO
  • Run demos and technical evaluations, often on the buyer's own data: discovery with their data team, how the data moves (warehouse shares, flat files, API) and a match test on their sample.

  • Run enterprise onboarding. Ingest first-party data, run routine scoring and get the customer's team live in our admin dashboard. Think of a pro sports team, from first file to first scored audience.

  • Build the simple pipelines and transformations onboarding needs, in SQL and light Python.

  • Carry the technical side of security reviews with our compliance lead, so questionnaires don't stall deals.

  • Write the playbook. Standard onboarding steps, reference setups and demo environments, so the next SA ramps in weeks.

  • Bring back what buyers asked for that we couldn't show, and tell product which gaps cost deals.

WHAT YOU HAVE
  • 3+ years in solutions engineering, solutions architecture, customer data onboarding or technical consulting, ideally at a martech, adtech, CDP, identity or analytics company, or an agency's data team.

  • Strong SQL. You've worked hands-on with customer data and the platforms it lives in.

  • You've run a demo for a skeptical data team and an onboarding for an enterprise customer, and both went well.

  • You're customer-centric to the core. You see every problem from the customer's side first.

  • You're calm and clear in a room of engineers looking for the hole.

  • You're in New York City or willing to relocate.

NICE TO HAVES
  • Some data science or data engineering background, enough to have opinions about how an experiment should be set up.

  • Snowflake, Big Query or Databricks, and how companies share data out of them.

  • Consumer data, identity resolution or marketing analytics.

  • Sports, financial services or travel.

WHAT THIS ISN'T
  • Custom modeling. When an account needs a custom pipeline or model, our forward deployed engineers build it, and you scope the hand-off.

  • Sales. The account executive owns the deal. You own whether it works.

WHAT SUCCESS LOOKS LIKE
  • First 90 days: you've run the technical evaluation and the onboarding on every account assigned to you without a founder in the room, and the first version of the onboarding playbook exists.

  • First 6 months: time from signed to first scored audience has a number and keeps falling. Every account you handed to an FDE went over with a scope they accepted as written.

  • The numbers you own: technical win rate on your evaluations and time-to-live on your…

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