Forward Deployed Engineer

About Minerva

Minerva builds AI for marketing leaders. Our platform allows marketers to focus on telling their brand's story while AI agents handle operationally intensive work such as data management, analytics, campaign generation, measurement, and reporting.

Everything is built on Minerva's proprietary consumer graph, an identity and attribute layer covering 270M+ U.S. consumers across 2,000+ time based attributes. Above this, we have two agentic systems built with OpenAI: an Agentic Data Engineer that unifies and standardizes a brand's first party data in hours, and an Agentic Data Scientist that trains robust targeting models at scale. Together, these systems enhance the quality of first party data, increase campaign performance, and give marketing teams back their time.

Our clients include leading consumer brands across categories: the NBA, Capital One, Hard Rock Stadium Group / Miami Dolphins, Wander, and Trust & Will. We have raised $20M from The General Partnership, 8VC, Lingotto, NBA Investments, Topology Ventures, Future Positive, Background Capital, and others.

About the Role

As a Forward Deployed Engineer, you are the engineer in the room when a customer's CMO, RevOps lead, and data team all ask, in different ways: "How do we actually get value out of Minerva's data inside our stack?"

You will own technical onboarding end to end. You will embed with our highest value brands, scope what "good" looks like with their commercial and technical stakeholders, and deliver work that maps their data into Minerva's golden model and activates it across their CRM, CDP, and ad platforms.

As we scale toward 100+ brands, you will both help each customer succeed and act as the field sensor signaling which integrations and agent behaviors to productize.

Your goal is to get a brand to real value in weeks, not quarters—thriving where there’s no playbook. You define what "good" looks like, set the goalposts with the customer, and build to them.

Key Responsibilities

• Own onboarding end to end, from first POC to production. Scope, design, and build the integration between Minerva's API and data, and the customer's stack (CRMs, CDPs, warehouses, ad platforms). Activate it where their team works: CRM, CDP, ad platforms, and agent facing access (MCP, natural language querying via our Agentic Data Scientist) for customers who want value without writing SQL.

• Build and standardize the brand's data models. Map source data (Shopify, HubSpot, Klaviyo) onto Minerva's golden model contracts, handle common source system challenges (inconsistent identifiers, deletes, multi tenant routing), and write validations to ensure data accuracy before a CMO sees a dashboard.

• Expand the brand's first party data asset and our ontology from the field. Identify entities, attributes, events, and behaviors not yet represented, map the customer's world onto Minerva's ontology, and specify what's genuinely new so it can become canonical. Your counterpart on the data platform team ensures safe integration.

• Sell the value and vision. Run discovery that doubles as a commercial conversation, make the case to a CMO or RevOps leader for what's worth building, demonstrate ROI, and drive land and expand within strategic accounts.

• Be the last line of technical defense. Debug production integrations, investigate data freshness and match rate issues, and resolve them quickly.

• Close the loop with product, surfacing field insights that shape API schema, data coverage, and roadmap, and flag integration patterns worth turning into platform primitives.

What Success Looks Like

• Within 30 days: Embedded with your first brand, source data mapped, and the goalposts for "good" set with stakeholders.

• By 60 days: The brand's first party data is in Minerva's golden model, validated, and activated in a system their team uses daily.

• By 90 days: A brand has moved from POC to a trusted production integration, with the next expansion opportunity identified.

Qualifications

• 3 to 6 years in analytics engineering or data science; you own the full path from raw source data to trusted model, decision, and business outcomes.

• SQL fluency and command of a transformation framework (SQLMesh or dbt). You build, test, and maintain a modeling layer, select the right grain and materialization, and write validations for accuracy before anyone sees a dashboard.

• Strong understanding of data modeling and ontology; you can map a customer's domain (Shopify, HubSpot, Klaviyo, a warehouse) onto a canonical model and pinpoint where the model falls short or what's genuinely new.

• Comfort with source system messiness—dealing with inconsistent identifiers, deletes, multi tenant routing, drift—and an instinct to solve root problems, not just tickets.

• Strong product analytics skills; you turn messy event and entity data into actionable metrics and design the pipelines that supply them.

• Customer facing and commercial instinct; you've partnered with customers (as an FDE, solutions or sales engineer, consultant, or TAM) and can sell. You make the ROI case, win over skeptical CMOs, and grow accounts, running discovery and value conversations seamlessly.

• Exceptional written and verbal communication; you handle both executive "why" and technical "how" conversations.

• Willing to work onsite in NYC and energized by wearing several hats on a lean, fast moving team.

Preferred

• Experience in marketing and sales modeling, marketing mix (MMM), multi touch attribution (MTA, deterministic and probabilistic), lead scoring, and routing.

• Familiarity with D2C unit economics.

You don't need to tick every box. If you're strong on the data side and hungry on the commercial side, or vice versa, we want to hear from you.

Compensation

Base salary: $160,000 to $200,000, commensurate with experience. Competitive equity package