About the job
About RevenueBase:
At RevenueBase, we are dedicated to building robust data infrastructure that enhances the trustworthiness of AI agents, minimizing errors.
We offer freshly updated and verified B2B data crucial for the effective operation of autonomous AI agents and go-to-market workflows.
Our company has experienced tremendous growth, tripling in size while achieving 100% gross dollar retention and maintaining a positive cash flow.
Our data powers AI solutions for major players like Clay, Zoominfo, and Dun & Bradstreet, as well as the next generation of AI-driven GTM tools.
Why This Position is Critical:
As our data platform rapidly scales, we are seeking a skilled engineer to take charge of data pipelines from start to finish, ensuring high data quality and robust reliability during our growth phase.
This role is essential for enhancing our data infrastructure, speeding up delivery through automation, and guaranteeing that our B2B clients receive reliable and timely data.
You will work on data systems that directly support our customers' workflows, where the dependability of pipelines and data quality are crucial for client retention.
Your Responsibilities:
Develop and maintain production-ready data pipelines utilizing DBT, Snowflake, and contemporary orchestration tools.
Take ownership of data engineering features from implementation to optimization and deployment.
Troubleshoot and enhance existing pipelines by identifying bottlenecks and improving performance.
Lead automation projects across the data stack to speed up delivery and minimize manual tasks.
Provide secondary support for B2B clients by investigating data discrepancies and clarifying edge cases, ensuring data reliability.
Design and implement new data import pipelines as we broaden our data source coverage.
Enhance data quality by implementing validation, monitoring, and testing processes to ensure accurate data delivery.
Participate in code reviews, architectural discussions, and contribute to data engineering best practices.
Your Profile:
You have over 3 years of professional experience in data engineering.
You possess strong skills in SQL, data modeling, Python, and ETL/ELT principles.

