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# Solutions Architect

- **Company:** Minerva Inc
- **Location:** New York, NY, United States
- **Experience:** Experienced
- **Salary:** $192,000 - $215,000
- **Contract:** Permanent contract
- **Skills:** Application Programming Interfaces (APIs), BigQuery, Customer Data Management, Information Engineering, Python (Programming Language), SQL Databases, Snowflake, Databricks
- **Published:** October 22, 2026
- **Apply:** https://www.indeed.com/viewjob?jk=a8de061327eb6707

## About the Role

* 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., * Some data science or data engineering background, enough to have opinions about how an experiment should be set up.
 * Snowflake, BigQuery or Databricks, and how companies share data out of them.
 * Consumer data, identity resolution or marketing analytics.
 * Sports, financial services or travel.

## Description

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., * 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., * 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 onboardings.