Data Engineer

Stuut is transforming accounts receivable for B2B companies—making collections smarter and faster for companies that have historically relied on manual processes that are labor intensive and costly. Our platform is gaining traction with finance teams across industrials, chemicals, and manufacturing sectors from Fortune 10 brands to scaling midmarkets. We're backed by top-tier investors including a16z, Khosla, Activant, 1984 Ventures and Page One.

We are hiring a Data Engineer to build the data foundation that powers Stuut's intelligence layer. You'll work closely with our product and engineering teams to transform raw financial data into actionable insights that help our customers get paid faster. This is a foundational role, you'll be our first data hire, which means you'll shape everything from our data architecture to how we think about analytics.

This is a high-impact role for someone who can think strategically about data infrastructure while rolling up their sleeves to build pipelines, models, and systems from scratch. You'll translate messy data into clean, reliable datasets that drive product decisions, customer insights, and business growth. If you've ever wanted to own the entire data stack at a fast-growing company, this is it.

• 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
  

• 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

Compensation

• Top-of-market salary and equity package

• Benefits (for U.S.-based full-time employees)

• Medical, dental & vision insurance coverage for you

• 401(k) & Match

• Equity

• Flexible PTO

• Parental Leave