revenuebase-inc - Data Engineer
Requirements
• You have 3+ years of professional data engineering experience. • Strong fundamentals in SQL, data modeling, Python and ETL/ELT principles. • DBT - hands-on experience building and maintaining transformation pipelines • AWS (S3, Lambda, Glue, etc.) • Prefect or similar orchestration tools (Airflow, Dagster) • Solid understanding of data quality principles, testing strategies, and monitoring practices. • 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 • Async-first mindset - can work independently, document decisions, and keep stakeholders informed without constant synchronous communication. • Async-first mindset • End-to-end ownership mentality - you see tasks through from planning to production, handling blockers and follow-through. • End-to-end ownership mentality • You care about data quality, pipeline reliability, and long-term maintainability.
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 - identify bottlenecks, resolve issues, and enhance performance. • 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. • 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. • Contribute to code reviews, architectural discussions, and data engineering best practices.
Benefits
• 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. • You'll work on data systems that directly power customer workflows - where pipeline reliability and data quality directly impact retention. • Product with real traction: Customers rely on our platform in production. • Product with real traction: • High ownership: Small team where your work directly shapes the product. • High ownership: • Engineering-driven culture: Quality and correctness matter. • Engineering-driven culture: • Growth stage company: Clear product-market fit and momentum. • Growth stage company: • Impact over process: Less bureaucracy, more building. • Impact over process: • 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.
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