Founding Analytics Engineer

Ambrook • New York, NY

1d

About The Position

Ambrook helps American family-run businesses become more profitable and resilient.
From volatile markets to climate shifts, independent operators face mounting pressure. While sustainable investments often yield the best long-term returns, they require financial clarity and capital that fragmented legacy systems can’t provide.
We are rebuilding the financial infrastructure that independent operators rely on. By replacing paperwork with modern tools for accounting, banking, and spending, Ambrook gives owners the data they need to prove viability to lenders and the next generation. We empower the stewards of land and labor to make confident investments in their future.
We’re a Series A startup backed by Thrive Capital, Dylan Field, and Homebrew. We’re looking for early team members to help us untangle the intersection of American industry, climate, and the economy.
We're looking for a Founding Analytics Engineer to own Ambrook's entire data function. You'll take an established warehouse and transform it into a clean, well-modeled, trustworthy foundation that enables every team and every agent to pull the right data with confidence.
You'll own the full stack from ingestion to insight and help build the function that will make every team at Ambrook fully data-driven.
We're looking for someone who we can count on to…
Own
The entire data layer downstream of production databases — warehouse, dbt models, Airbyte pipelines, orchestration — plus primary company-wide dashboards, data access patterns for AI agents, and an advisory role on data modeling in external systems (e.g., HubSpot) to keep upstream data clean.
Teach
Data literacy across the company — how to think about metrics, write better queries, and self-serve in Hex. Best practices for structuring data in the tools teams own. Metrics definitions and consistency so the team asks the right questions of the data.
Improve
The data model. Grow our capacity by resolving gotchas, improving documentation, and building trust. Enable teams to self-serve on reliable data.

Requirements

• Proven experience as a solo or early data hire. You've owned the full stack and built infrastructure or the function from scratch.
• Advanced SQL and production dbt, with hands-on experience in a cloud warehouse (BigQuery or similar) and ETL tools (Airbyte or comparable.)
• Strong business instincts. You translate ambiguous questions into clean data models and communicate findings clearly to non-technical teammates.
• Comfortable in fast-moving environments with high-volume sales funnels.
• AI-native approach to data work. You think in terms of agent automation (quality checks, column generation, automated reviews) and actively use AI tools to move faster.

Nice To Haves

• Experience with Airbyte, Hex, and/or BigQuery.
• Experience with Airflow or Dagster for orchestration.
• Basic ML or statistical modeling experience.

Responsibilities

• Own the entire data layer downstream of production databases — warehouse, dbt models, Airbyte pipelines, orchestration — plus primary company-wide dashboards, data access patterns for AI agents, and an advisory role on data modeling in external systems (e.g., HubSpot) to keep upstream data clean.
• Teach data literacy across the company — how to think about metrics, write better queries, and self-serve in Hex. Best practices for structuring data in the tools teams own. Metrics definitions and consistency so the team asks the right questions of the data.
• Improve the data model. Grow our capacity by resolving gotchas, improving documentation, and building trust. Enable teams to self-serve on reliable data.

What This Job Offers

• Job Type: Full-time
• Career Level: Mid Level
• Education Level: No Education Listed