Data Engineer & Architect

RevenueBase:

• 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've tripled growth while maintaining 100% gross dollar retention and staying cashflow positive.

• We power AI agents for Clay, Orbital, 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 experienced data engineers and architects who can design systems that handle massive data volumes reliably and efficiently.

• This role exists to strengthen our core data infrastructure, improve scalability and correctness, and ensure our datasets remain accurate, fresh, and trusted as customer usage grows.

• You’ll work on a platform where data quality, reliability, and architecture directly impact customer trust and retention.

What You'll Do:

• Design, build, and maintain scalable data pipelines handling high-volume structured and semi-structured data.

• Own data infrastructure end-to-end, from ingestion and storage through transformation, validation, and delivery.

• Architect and optimize data systems using Snowflake, S3, and modern cloud data stacks.

Ensure data freshness, accuracy, and consistency across production systems.

• Collaborate closely with backend, frontend, and AI engineers to support product and customer use cases.

• Define and enforce best practices around data modeling, schema design, and data quality checks.

• Continuously improve performance, cost efficiency, observability, and reliability of the data platform.

• Help raise the overall data engineering bar as the company and datasets scale.

Who You Are:

• You have 5+ years of professional experience in data engineering and/or data architecture roles.

• Strong fundamentals in data modeling, ETL/ELT design, and distributed data systems.

• Hands-on experience with:

• Snowflake

• Cloud object storage (AWS S3 or equivalent)

• High-volume batch and/or streaming data pipelines

• SQL and data transformation frameworks

• Solid understanding of:

• Data warehousing concepts

• Data reliability, validation, and observability

• Cloud infrastructure and cost-performance tradeoffs

• Experience working with large-scale, frequently updated datasets.

• Comfortable operating in a fast-moving, remote-first environment.

• You take ownership, communicate clearly, and design systems meant to last.

• Preferred (not required):

• Familiarity with B2B data, GTM data, or enrichment pipelines

• Experience supporting AI/ML or agent-driven workflows

Why RevenueBase:

• Product with real traction: Customers rely on our platform in production.

• High ownership: Small team where your work directly shapes the product.

• Engineering-driven culture: Quality and correctness matter.

• Growth stage company: Clear product-market fit and momentum.

• Impact over process: Less bureaucracy, more building.

What We Offer:

• Competitive compensation based on experience.

• Meaningful ownership and long-term growth opportunities.

• Flexible working hours.

• Fully remote-friendly team.

• Direct collaboration with founders and core engineering leadership.