Data Engineer

• Design, build, and maintain scalable data pipelines using modern ETL/ELT tools.
• Manage and optimize our data warehouse infrastructure (Snowflake) for performance, cost, and reliability.
• Develop and maintain data models that support analytics, reporting, and machine learning use cases.
• Build systems that make key business metrics easily accessible - including net new ARR, MRR, trial-to-paid conversion, churn rates, gross and net revenue retention.
• Implement data quality monitoring, testing frameworks, and alerting systems.
• Partner with Product and Engineering to instrument event tracking and ensure data completeness across the customer journey.
• Build and maintain integrations between production systems (including payments infrastructure, CRM, analytics tools) and the data warehouse.
• Support revenue operations and go-to-market teams with clean, reliable data for tracking performance and customer behavior.
• Enable better segmentation and analysis to support vertical personalization and moving upmarket.
• Establish data governance standards, documentation practices, and access controls.
• Optimize query performance and support analysts with data infrastructure needs.
• Surface insights and trends from data to help teams make smarter, faster decisions.
• Evaluate and implement new data tools and technologies to improve our data stack.

Data Engineer

Data Engineer

Senior Data Engineer

Junior Data Engineer

Data Engineer, Databricks

Data Architect – Microsoft Azure, Microsoft Fabric