# Data Engineer

**Company:** [Braintrust](https://hotfix.jobs/companies/braintrust)
**Location:** San Francisco, CA, New York, NY
**Role:** Data Engineering
**Experience:** 10+ years
**Skills:** SQL, Data Modeling, Data Pipelines, Orchestration, Data Transformation, Product Telemetry, CRM, Billing Systems, Customer Health Data, Marketing Analytics, Finance Data, Support Systems, Dashboarding, Self-Serve Reporting, AI Tools
**Posted:** 2026-06-19

> Hands-on Data Engineer building the core data layer for a fast-growing AI observability startup. Own data models, pipelines, and trusted metrics across product usage, revenue, and GTM systems while partnering with Sales, RevOps, Marketing, and Finance.

## Job Description

## What You Will Do
- Build and own the core data models that connect product usage, accounts, customers, revenue, pipeline, billing, and customer health.
- Create trusted sources of truth for the metrics Braintrust uses to run the business, including activation, usage, retention, expansion, pipeline, ARR, and usage-based revenue.
- Build pipelines across product telemetry, CRM, billing, customer success, marketing, support, finance, and AI-powered internal systems.
- Partner with Engineering and Product to improve the quality, consistency, and usability of product data.
- Partner with Sales, RevOps, Marketing, and Finance to turn messy operational questions into durable data models and workflows.
- Build dashboards, datasets, and self-serve reporting that help teams answer common questions without relying on one-off analysis.
- Use AI to speed up your own work and identify where agents can reduce manual reporting, enrichment, QA, routing, research, and operational follow-up.
- Help design the data layer for future AI-native business operations workflows, including clean context, structured inputs, feedback loops, and evaluation of outputs.
- Improve data quality through testing, monitoring, documentation, lineage, and clear ownership.
- Support business planning and operating cadence by making sure leadership has accurate visibility into customer usage, GTM performance, and revenue health.
- Make pragmatic tradeoffs between foundational architecture and urgent business questions.

## About You
- 10+ years in data engineering, analytics engineering, data architecture, or business systems data roles.
- Excellent communication skills and ability to work across technical and non-technical teams.
- Strong experience building data systems in developer tools, infrastructure, AI, or another technical environment.
- Deep experience with SQL, data modeling, pipelines, orchestration, transformation, and production-grade code.
- Experience working across product telemetry, CRM, billing, customer health, marketing, support, finance, or other operational systems.
- Strong understanding of how GTM teams operate, especially Sales, RevOps, Marketing, and Finance.
- Deep curiosity about AI and a strong point of view on how it will change data engineering, analytics, and business operations.
- Hands-on experience using AI tools in your own work to write code, analyze data, automate workflows, improve documentation, or accelerate operational tasks.
- Comfortable designing systems where humans and agents work together, with the right data, context, guardrails, and feedback loops.
- Comfortable operating as the only data hire in a startup environment, balancing foundational architecture with urgent business needs.

## Bonus Points
- Worked at a high-growth startup where the data function was still being built.
- Experience with enterprise and self-serve revenue motions.
- Experience with usage-based pricing, consumption models, product-led growth, or sales-assisted funnels.
- Built customer health, activation, retention, expansion, forecasting, or revenue intelligence systems.
- Supported enterprise sales motions, including account scoring, pipeline analytics, territory planning, renewal workflows, or expansion reporting.
- Built or used agents for internal operations, data QA, customer research, enrichment, reporting, or workflow automation.
- Experience in AI, developer tools, infrastructure, observability, or data platform companies.

## Benefits
- Medical, dental, and vision insurance
- Daily lunch, snacks, and beverages
- Flexible time off
- Competitive salary and equity
- AI Stipend

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