Forward Deployed Engineer, Data Systems

About Minerva

Minerva builds AI for marketing leaders. Our platform allows marketers to focus on telling their brand's story, delegating operationally intensive tasks to our AI agents which handle 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 1,000+ temporal attributes. We have two agentic systems built through an OpenAI research partnership: 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, Ramp, 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.

Responsibilities

• Own onboarding end to end, from first POC to production.
• Quickly grok the company's pain points and generate immediate impact for their marketing team.
• Steer our Agentic Data Engineer to build and standardize the brand's data models.
• Map source integrations onto Minerva's golden model contracts, handle common data quality failure modes, and write validations to ensure data accuracy before a CMO sees a dashboard.
• Expand the connectivity between the customer's first-party data and our third-party data. Identify entities, attributes, events, and behaviors not yet represented, building pipes for key marketing product features e.g., Attribution, Personalization, Conversion Rate Optimization.
• Work with other data engineers to ensure systems become robust and battle-tested.
• Systemize custom workflows for a given customer into repeatable, agentically-generated pipelines within our orchestration framework.
• 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.

Our Data Stack: Dagster for all things orchestration, dbt-core within Dagster as the primary data transformation surface, Modal for ML engineering, and frontier models & agent SDKs.

Requirements

• At least 2 years in analytics engineering, data engineering, or data science; you own the full path from raw source data to trusted model, decision, and business outcomes.
• Customer-facing and commercial instinct; you've partnered with customers (as an FDE, solutions or sales engineer, consultant) and can sell. You make the ROI case, win over skeptical CMOs, and grow accounts, running discovery and value conversations seamlessly.
• SQL fluency, data engineering principles, and command of a transformation framework (e.g., dbt). You've built, tested, and maintained a modeling layer, select the right grain and materialization, and write validations for accuracy before anyone sees a dashboard.
• 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.
• Heavy and efficient use of AI coding tools (Claude Code, Cursor, etc.) as a force multiplier.

Preferred Experience

• Experience in marketing and sales modeling, marketing mix (MMM), multi-touch attribution (MTA), customer LTV, lead scoring, and lead routing.
• Experience with an orchestrator such as Airflow, Dagster, Prefect, etc.
• Real software engineering experience: you're comfortable with infrastructure and working within larger production systems rather than a constrained SQL-only role.
• Have been embedded within a product team.
• Familiarity with D2C unit economics.
• Prior early-stage startup experience.

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.

Pay

Base salary: $170,000 to $220,000, commensurate with experience. Competitive equity & a marquee benefits package.