Data Engineer

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 by identifying bottlenecks and enhancing performance
• Drive automation initiatives across the data stack to reduce manual interventions
• Provide 2nd line support for B2B customers to investigate data issues and edge cases
• Design and implement new data import pipelines to expand data source coverage
• Implement data quality improvements including validation, monitoring, and testing
• 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
• Hands-on experience building and maintaining transformation pipelines with DBT
• Solid understanding of data quality principles, testing strategies, and monitoring practices
• Strong communication skills for technical and non-technical stakeholders
• Async-first mindset and ability to work independently in a remote environment
• End-to-end ownership mentality

Preferred Qualifications

• Experience with Snowflake
• Experience with Databricks
• Experience with AWS (S3, Lambda, Glue, etc.)
• Experience with orchestration tools like Prefect, Airflow, or Dagster

About the Company

RevenueBase builds the data infrastructure that makes AI agents trustworthy. We provide continuously refreshed, verified B2B data for autonomous AI agents and GTM workflows, powering industry leaders like Clay, Zoominfo, and Dun & Bradstreet.