Data Engineer

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