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Full-time
Medical Insurance, Dental Insurance, Vision Insurance, Daily Lunch, Snacks, Beverages
Posted 28d ago
~40 hrs/week
Responsibilities
Build and own core data models and pipelines connecting product usage, revenue, and customer health to create trusted sources of truth. Partner with GTM and Engineering teams to automate operational workflows and design the data layer for AI-native business operations.
Requirements
Requires 10+ years of experience in data engineering or architecture with deep expertise in SQL and production-grade code. Must have a strong understanding of GTM operations and hands-on experience using AI tools to accelerate data workflows.
Full job description
About the company
Braintrust is the AI observability platform. By connecting evals and observability in one workflow, Braintrust gives builders the visibility to understand how AI behaves in production and the tools to improve it.
Teams at Notion, Stripe, and Vercel use Braintrust to compare models, test prompts, and catch regressions — turning production data into better AI with every release.
About the Role
Braintrust is growing quickly across enterprise and self-serve customers, and our internal systems need to scale with us. You will build and own the data infrastructure that will power how our business operations and systems function. This is a hands-on, solo role for now. You won't be joining a team with mature processes already in place. You'll be building the queues, workers, and data models, on top of a warehouse that already has solid foundations (health scoring, ARR movement, engagement facts) but no activation layer.
The right person has strong technical depth, understands how GTM teams work, and is excited to build with AI. You should have strong opinions about where agents can automate operational workflows, and the judgment to build the data systems, context, and feedback loops that make those workflows work.
You'll partner with Product and Engineering on usage data and event schemas, and work directly with Sales, RevOps, Marketing, and Finance to turn one-off requests into reusable platform primitives (routing rules, scoring models, activation contracts) instead of one-off scripts.
What You Will Do
Build and own the customer data platform: a company/event/signal spine that resolves identity across Salesforce, product, and marketing sources into one queryable universe.
Design the queues, workers, and models that power enrichment, account routing/assignment, and activation
Build the account scoring and routing engine that determines account ownership (AE-owned vs. house/hedge pools), with every decision explainable and reversible.
Integrate external data sources across CRM, sales engagement, ads, and enrichment/intent vendors, and handle vendor APIs, web hooks, and rate limits.
Push signal outward, not just model it. Reverse-ETL into Salesforce, Slack digests that surface risk and opportunity before someone has to go looking, eventually activation into ad platforms.
Partner with Engineering and Product on usage data and event schemas as the product surface grows.
Design row- and column-level governance (who can see which accounts, which fields) as a first-class part of the data model, not an afterthought bolted onto Snowflake permissions later.
Debug production issues across the full path: Snowflake, dbt, orchestration, vendor APIs, web hooks, and the downstream systems (Salesforce, Slack) that depend on the output being right.
Use AI to accelerate your own build, and design the data layer (clean context, structured inputs, feedback loops) that future GTM agents (account research, pre-call prep, follow-up) will run on top of.
About You
You’ve built data platforms, backend systems, workflow engines, or data/ML infrastructure. This is a platform-engineering role, not a dashboards-and-reporting role.
Deep experience with analytical data systems: Snowflake, dbt, and an orchestrator (Dagster, Airflow, or similar).
Comfortable writing production backend code, not just SQL. This role involves queues, workers, and stateful jobs (e.g., on AWS Batch/Lambda), not only transformation models.
Clear judgment about data modeling, schema evolution, contracts, and lineage, with an instinct for what happens to a model six months after you ship it.
You care whether a workflow actually works end to end: whether the rep trusts the Slack ping, whether the routed account was routed for a reason someone can state in one sentence.
Strong debugging instincts across a multi-system path: a broken pipeline could be a bad vendor payload, a Fivetran sync gap, a dbt model, or a downstream Salesforce write. You enjoy finding out which.
Strong understanding of how GTM teams (Sales, RevOps, Marketing) operate, enough to know why "respect the existing owner" matters more than a clever score.
Comfortable operating as the only data hire, balancing foundational architecture with urgent business needs.
Bonus Points
You've built a customer data platform, account routing/scoring engine, or activation layer before, especially at a company with both self-serve and enterprise sales motions.
You've worked with usage-based pricing, consumption models, or PLG-plus-sales-assisted funnels.
You've built or used agents for internal operations, enrichment, research, or workflow automation.
Experience with our stack, or close equivalents: Snowflake, dbt, Dagster, AWS Batch/Lambda, Fivetran, Terraform, GitHub Actions, Soda, or semantic-layer tools like Omni or Looker.
Braintrust user :)
What Success Looks Like
Braintrust has a governed spine (company, event, signal) that Sales, RevOps, Marketing, and Finance all build on top of.
Signals that used to get lost in a dashboard now reach a rep or a system automatically, with an audit trail for every automated decision.
Any rep can be told in one sentence why they own an account.
The platform reaches accounts that exist in the warehouse but never made it into the CRM, closing the reach gap between what you know and what you can act on.
AI is a real operating layer on top of this data: agents doing account research, prep, and follow-up on a foundation of clean, governed context, not a side experiment bolted onto a spreadsheet.
The stack stays simple enough for a startup team to run solo, while being structured enough to hand off to a business-systems team as it grows.
Benefits include
Medical, dental, and vision insurance
Daily lunch, snacks, and beverages
Flexible time off
Competitive salary and equity
Wifi & cellphone stipend
Equal opportunity
Braintrust is an equal opportunity employer. All applicants will be considered for employment without attention to race, color, religion, sex, sexual orientation, gender identity, national origin, veteran or disability status.
AI-powered hiring platform for AI interviews, candidate matching, and a global talent marketplace.
Industry
Technology, Information and Internet
Company size
11-50 employees
Founded
2018
Headquarters
San Francisco, California
LinkedIn followers
974,345
Total funding
$128M
Braintrust is revolutionizing hiring with Braintrust AIR, the world's first and only end-to-end AI recruiting platform. Trained with human insights and proprietary data, Braintrust AIR reduces time to hire from months to days, instantly matching you with pre-vetted qualified candidates, and conducting the first round phone screen for you. Trusted by hundreds of Fortune 1000 enterprises including Nestlé, Porsche, Atlassian, Goldman Sachs, and Nike, Braintrust AIR is making talent acquisition professionals 100x more effective and saving companies hundreds of thousands of dollars in recruiting costs.
Offices: 1 Main St, San Francisco, California 94105, US
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