Data Engineer

Role overview This is an experienced data engineering role on a data team, focused on building and scaling pipelines, establishing best practices and data quality, and enabling self-service data access across engineering, revenue operations, growth, and adjacent functions. The work spans the full path from ingestion through to delivery, plus developing AI agents that field data questions on behalf of others.

Responsibilities - Own and streamline data pipelines from ingestion through to delivery, keeping them reliable, scalable, and efficient. - Implement and maintain dbt standards, modeling conventions, and quality controls. - Build self-service tooling and write clear documentation that lets cross-functional teams meet their own data needs independently. - Create AI agents that answer data questions for other teams.

Requirements - Demonstrated experience formalizing and scaling data pipelines, ideally as one of the first or early data engineers on a growing team. - Expert-level knowledge of dbt. - Proficiency across the modern data stack, including Python, SQL, and BI tools. - Structured thinking and the ability to simplify complex, messy data into clear models. - Strong ability to understand varied stakeholder requirements and build generalized solutions.

Benefits and work setup - Remote-friendly role that can be executed globally. - Optional in-office work from hubs including London, Warsaw, and New York. - Annual discretionary learning and development budget. - Annual discretionary social travel stipend for meeting colleagues. - Annual company offsite bringing the whole team together. - Monthly co-working stipend for those outside main hubs.