Data Engineer

RevenueBase Inc

WorldwideremotePosted 27 days ago

Skill Required

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Key highlights

3+ years of professional data engineering experience
Must have DBT experience
Fully remote-friendly team
Competitive compensation based on experience

Role overview

RevenueBase is building the data infrastructure that makes AI agents trustworthy instead of error-prone, providing continuously refreshed, verified B2B data for autonomous AI agents and GTM workflows. The company has tripled growth while maintaining 100% gross dollar retention and staying cashflow positive, powering AI agents for Clay, Zoominfo, Dun & Bradstreet, and the next generation of AI GTM tools. This role exists to strengthen data infrastructure, accelerate delivery through automation, and ensure B2B customers receive accurate, timely data they can trust. The engineer will own pipelines end-to-end, keep data quality high, and ensure reliability as the platform scales rapidly, working on systems where pipeline reliability and data quality directly impact retention.

Responsibilities

Build and maintain production-ready data pipelines using DBT, Snowflake, and modern orchestration tools.
Own data engineering features end-to-end, from implementation through optimization and deployment.
Fix and improve existing pipelines - identify bottlenecks, resolve issues, and enhance performance.
Drive automation initiatives across the data stack to accelerate delivery and reduce manual interventions.
Provide 2nd line support for B2B customers - investigate data issues, clarify edge cases, and ensure customers can trust their data.
Design and implement new data import pipelines as we expand our data source coverage.
Implement data quality improvements - validation, monitoring, and testing to ensure reliable, accurate data delivery.
Contribute to code reviews, architectural discussions, and data engineering best practices.

Requirements

3+ years of professional data engineering experience.
Strong fundamentals in SQL, data modeling, Python and ETL/ELT principles.
DBT - hands-on experience building and maintaining transformation pipelines
Solid understanding of data quality principles, testing strategies, and monitoring practices.
Comfortable working in a fast-moving, remote-first environment.
Strong communicator - able to explain technical issues clearly to both technical and non-technical stakeholders.
Async-first mindset - can work independently, document decisions, and keep stakeholders informed without constant synchronous communication.
End-to-end ownership mentality - you see tasks through from planning to production, handling blockers and follow-through.
You care about data quality, pipeline reliability, and long-term maintainability.