Data Engineer
Build and scale reliable data pipelines for the Growth team, establish dbt and data-quality standards, and enable self-service analytics across cross-functional teams. The role requires strong data engineering experience, expert dbt knowledge, and proficiency in Python and SQL.
About the job
Responsibilities
- Own and streamline data pipelines from ingestion to delivery, ensuring they are reliable, scalable, and efficient.
- Implement and maintain dbt best practices, data standards, and quality controls.
- Build self-service tooling and write clear documentation to empower cross-functional teams, including Engineering, Revenue Operations, and Growth, to independently meet their data needs.
- Create AI agents to serve data questions for others.
Requirements
- Demonstrated experience formalizing and scaling data pipelines, ideally as one of the first or early data engineers on a growing team.
- Expert knowledge of dbt.
- Proficiency with tools across the modern data stack, including Python, SQL, and BI tools.
- Structured thinking and the ability to simplify complex, messy data into clear structures.
- Strong ability to understand varied stakeholder requirements and build generalized solutions.
Benefits
- Annual discretionary learning and development stipend.
- Annual discretionary social travel stipend.
- Annual company offsite.
- Monthly coworking stipend for employees not located near a main hub.
Skills
dbt, Python, SQL, BI Tools, Data Pipelines, Data Quality, Data Modeling, AI Agents
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