Data Engineer

Stuut is transforming accounts receivable for B2B companies, and they are seeking a Data Engineer to build the data foundation that powers their intelligence layer. This role involves designing data infrastructure, creating analytics foundations, and implementing DataOps best practices to drive strategic decisions and business growth.

Responsibilities:

• Build and own our data infrastructure from the ground up, design pipelines that ingest, transform, and model data from customer ERPs, payment processors, and internal systems
• Partner with product and engineering to embed data quality and observability into everything we ship
• Create the analytics foundation that helps our customers understand payment patterns, collection trends, and cash flow predictions
• Implement DataOps best practices to ensure our data is timely, accurate, and trusted across the organization
• Collaborate with leadership to define KPIs, build dashboards, and surface insights that drive strategic decisions
• Scale our data platform as we grow from dozens to hundreds of customers, anticipating needs before they become bottlenecks

Requirements:

• Have 3+ years of hands-on experience building production data pipelines using Python
• Know your way around SQL and modern data warehouses; bonus if you've worked with Snowflake, BigQuery, or Redshift
• Have experience implementing ETL/ELT workflows at scale using tools like Airflow, dbt, or similar
• Understand data modeling fundamentals and can design schemas that balance performance with flexibility
• Have worked with messy, real-world data from SaaS APIs, databases, or third-party integrations
• Thrive in ambiguity and get energized by building something new rather than inheriting someone else's stack
• Care deeply about data quality and believe that great analytics start with great infrastructure
• Have experience (or strong interest) in fintech, B2B SaaS, or financial data, understanding AR/AP workflows is a big plus