Data Engineer
RevenueBase:
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We're building the data infrastructure that makes AI agents trustworthy instead of error-prone.
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We provide continuously refreshed, verified B2B data for autonomous AI agents and GTM workflows.
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We've tripled growth while maintaining 100% gross dollar retention and staying cashflow positive.
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We power AI agents for Clay, Zoominfo, Dun & Bradstreet, and the next generation of AI GTM tools.
Why We're Hiring This Role:
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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.
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This role exists to strengthen our data infrastructure, accelerate delivery through automation, and ensure our B2B customers receive accurate, timely data they can trust.
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You'll work on data systems that directly power customer workflows - where pipeline reliability and data quality directly impact retention.
What You'll Do:
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Build and maintain production-ready data pipelines using DBT, Snowflake, and modern orchestration tools.
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Own data engineering features end-to-end, from implementation through optimization and deployment.
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Fix and improve existing pipelines - identify bottlenecks, resolve issues, and enhance performance.
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Drive automation initiatives across the data stack to accelerate delivery and reduce manual interventions.
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Provide 2nd line support for B2B customers - investigate data issues, clarify edge cases, and ensure customers can trust their data.
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Design and implement new data import pipelines as we expand our data source coverage.
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Implement data quality improvements - validation, monitoring, and testing to ensure reliable, accurate data delivery.
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Contribute to code reviews, architectural discussions, and data engineering best practices.
Who You Are:
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You have 3+ years of professional data engineering experience.
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Strong fundamentals in SQL, data modeling, Python and ETL/ELT principles.
Must have:
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DBT - hands-on experience building and maintaining transformation pipelines
Nice to have:
- Snowflake
- Databricks
- AWS (S3, Lambda, Glue, etc.)
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Prefect or similar orchestration tools (Airflow, Dagster)
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Solid understanding of data quality principles, testing strategies, and monitoring practices.
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Comfortable working in a fast-moving, remote-first environment.
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Strong communicator - able to explain technical issues clearly to both technical and non-technical stakeholders.
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Async-first mindset - can work independently, document decisions, and keep stakeholders informed without constant synchronous communication.
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End-to-end ownership mentality - you see tasks through from planning to production, handling blockers and follow-through.
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You care about data quality, pipeline reliability, and long-term maintainability.
Why RevenueBase:
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Product with real traction: Customers rely on our platform in production.
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High ownership: Small team where your work directly shapes the product.
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Engineering-driven culture: Quality and correctness matter.
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Growth stage company: Clear product-market fit and momentum.
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Impact over process: Less bureaucracy, more building.
What We Offer:
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Competitive compensation based on experience.
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Meaningful ownership and long-term growth opportunities.
- Flexible working hours.
- Fully remote-friendly team.
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Direct collaboration with founders and core engineering leadership.
Originally posted on Himalayas