Data Engineer

RevenueBase:
* We're building the data infrastructure that makes AI agents trustworthy instead of error-prone.
We're building the data infrastructure that makes AI agents trustworthy instead of error-prone.
* We provide continuously refreshed, verified B2B data for autonomous AI agents and GTM workflows.
We provide continuously refreshed, verified B2B data for autonomous AI agents and GTM workflows.
* We've tripled growth while maintaining 100% gross dollar retention and staying cashflow positive.
We've tripled growth while maintaining 100% gross dollar retention and staying cashflow positive.
* We power AI agents for Clay, Zoominfo, Dun & Bradstreet, and the next generation of AI GTM tools.
We power AI agents for Clay, Zoominfo, Dun & Bradstreet, and the next generation of AI GTM tools.

Why We're Hiring This Role:
* Our data platform is scaling rapidly, and we need engineer who can own pipelines end-to-end, keep data quality high, and ensure reliability as we grow.
Our data platform is scaling rapidly, and we need engineer who can own pipelines end-to-end, keep data quality high, and ensure reliability as we grow.
* This role exists to strengthen our data infrastructure, accelerate delivery through automation, and ensure our B2B customers receive accurate, timely data they can trust.
This role exists to strengthen our data infrastructure, accelerate delivery through automation, and ensure our B2B customers receive accurate, timely data they can trust.
* You'll work on data systems that directly power customer workflows - where pipeline reliability and data quality directly impact retention.
You'll work on data systems that directly power customer workflows - where pipeline reliability and data quality directly impact retention.

What You'll Do:
* Build and maintain production-ready data pipelines using DBT, Snowflake, and modern orchestration tools.
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.
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.
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.
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.
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.
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.
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.
Contribute to code reviews, architectural discussions, and data engineering best practices.

Who You Are:
* You have 3+ years of professional data engineering experience.
You have 3+ years of professional data engineering experience.
* Strong fundamentals in SQL, data modeling, Python and ETL/ELT principles.
Strong fundamentals in SQL, data modeling, Python and ETL/ELT principles.

Must have:
* DBT- hands-on experience building and maintaining transformation pipelines
DBT- hands-on experience building and maintaining transformation pipelines

Nice to have:
* Snowflake

Snowflake
* Databricks

Databricks
* AWS (S3, Lambda, Glue, etc.)

AWS (S3, Lambda, Glue, etc.)
* Prefect or similar orchestration tools (Airflow, Dagster)
Prefect or similar orchestration tools (Airflow, Dagster)
* Solid understanding of data quality principles, testing strategies, and monitoring practices.
Solid understanding of data quality principles, testing strategies, and monitoring practices.
* Comfortable working in a fast-moving, remote-first environment.
Comfortable working in a fast-moving, remote-first environment.
* Strong communicator- able to explain technical issues clearly to both technical and non-technical stakeholders.
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.
Async-first mindset- can work independently, document decisions, and keep stakeholders informed without constant synchronous communic