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RevOS Data Engineering Agent
Build a production data layer without a data engineer
Ship a revenue/growth data layer in an afternoon instead of hiring a data engineer. Tell Claude Code what you need in plain English; it writes the dbt models and semantic layer against your real schema. The agent fails at review time, not in production — you ship the diff.
We kept watching teams point an AI agent at their data and get back confident, wrong answers.
The model wasn't the problem. It had no idea what your "revenue" or "active user" actually means, so it guessed.
So we built the RevOS Data Engineering Agent.
One command sets up a full stack (dbt, Cube, BigQuery, Git), and Claude Code builds your models against your real schema, not a blank file. The agent proposes the work, you review the diff, and you stay in control of what ships.
Copilot writes code. RevOS gives the agent the context to know which code is right. Different thing, and they compose.
A production data layer you can build in an afternoon, without hiring a data engineer.
Free to start, no credit card.
Supported path today is BigQuery + dbt.
I'll be around all day, happy to answer anything and hear your honest feedback 🙏
About RevOS Data Engineering Agent on Product Hunt
“Build a production data layer without a data engineer”
RevOS Data Engineering Agent was submitted on Product Hunt and earned 8 upvotes and 2 comments, placing #62 on the daily leaderboard. Ship a revenue/growth data layer in an afternoon instead of hiring a data engineer. Tell Claude Code what you need in plain English; it writes the dbt models and semantic layer against your real schema. The agent fails at review time, not in production — you ship the diff.
On the analytics side, RevOS Data Engineering Agent competes within Developer Tools, Artificial Intelligence and Data & Analytics — topics that collectively have 994.2k followers on Product Hunt. The dashboard above tracks how RevOS Data Engineering Agent performed against the three products that launched closest to it on the same day.
Who hunted RevOS Data Engineering Agent?
RevOS Data Engineering Agent was hunted by Renat Zubairov. A “hunter” on Product Hunt is the community member who submits a product to the platform — uploading the images, the link, and tagging the makers behind it. Hunters typically write the first comment explaining why a product is worth attention, and their followers are notified the moment they post. Around 79% of featured launches on Product Hunt are self-hunted by their makers, but a well-known hunter still acts as a signal of quality to the rest of the community. See the full all-time top hunters leaderboard to discover who is shaping the Product Hunt ecosystem.
For a complete overview of RevOS Data Engineering Agent including community comment highlights and product details, visit the product overview.
Renat Zubairov
Hi Product Hunt 👋 I'm Renat, founder of RevOS.
We kept watching teams point an AI agent at their data and get back confident, wrong answers.
The model wasn't the problem. It had no idea what your "revenue" or "active user" actually means, so it guessed.
So we built the RevOS Data Engineering Agent.
One command sets up a full stack (dbt, Cube, BigQuery, Git), and Claude Code builds your models against your real schema, not a blank file. The agent proposes the work, you review the diff, and you stay in control of what ships.
Copilot writes code. RevOS gives the agent the context to know which code is right. Different thing, and they compose.
A production data layer you can build in an afternoon, without hiring a data engineer.
Free to start, no credit card.
Supported path today is BigQuery + dbt.
I'll be around all day, happy to answer anything and hear your honest feedback 🙏