About the role
At Stuut, a company specializing in AI-driven order-to-cash solutions for major enterprises, the data engineer role is pivotal in establishing the data infrastructure that supports their intelligence platform. The company serves over 150 clients, including Fortune 50 firms, and focuses on optimizing financial workflows such as credit, collections, and payments. This position is the first dedicated data hire, offering a unique opportunity to shape the entire data architecture and analytics approach from the ground up.
The data engineer will collaborate closely with product and engineering teams to transform complex financial data into actionable insights that accelerate cash flow for customers. Responsibilities include designing and building data pipelines, creating a unified semantic layer for consistent metrics, and implementing data quality and observability practices. The role demands hands-on work with ETL/ELT workflows, data modeling, and integration of diverse data sources like ERPs and payment processors, ensuring the data platform scales effectively as the company grows.
Ideal candidates have over five years of experience with Python-based data pipelines, proficiency in SQL and cloud data warehouses such as Snowflake or BigQuery, and familiarity with tools like dbt and Airflow. Experience with fintech or financial data, especially accounts receivable/payable workflows, is advantageous. The position is full-time and onsite in San Francisco or New York City, offering competitive compensation and benefits, and emphasizes diversity and inclusion in its hiring practices.