Data Engineer

stuut-ai; San Francisco (CA); On-site; USD 180,000 - 230,000; Full time

Benefits offered by this job

Top-of-market salary and equity

Medical, dental & vision coverage

401(k) & Match

Equity

Flexible PTO

Parental Leave

Job summary

Stuut is building the data foundation that powers its AI-driven finance platform. As our first data hire, you’ll partner with product and engineering to transform raw financial data into reliable datasets, pipelines, and models that guide product decisions and customer outcomes.

From canonical schemas to observability and DataOps, you’ll own end-to-end data stack design, deliver scalable pipelines from ERP and payments feeds, and collaborate with ML teams to unlock timely insights for customers.

Qualifications

• 3+ years building production data pipelines with Python.
• Strong SQL and cloud data warehouses (Snowflake/BigQuery a plus).
• ETL/ELT workflows at scale using dbt, Airflow, or similar.
• Built or contributed to a semantic/metrics layer with consistency.
• Data modeling fundamentals; canonical schemas for messy data.
• Experience with real-world SaaS data, ERPs, APIs; fintech familiarity.

Responsibilities

• Build and own data infrastructure from the ground up, ingesting data from ERPs, payment processors, and internal systems.
• Create transformation and semantic layers serving analytics, reporting, and AI/ML systems.
• Design canonical data models with quality tests and observability by default.
• Build event and signal pipelines turning interactions into clean, labeled data.
• Embed data quality, lineage, and observability with product and ML teams.
• Apply DataOps best practices to keep data timely, accurate, and trusted.
• Collaborate with leadership to define KPIs, dashboards, and actionable insights.
• Scale the data platform as customer base grows from dozens to hundreds.

Skills

Python

SQL

dbt/Airflow

Data modeling

Data quality

Analytics

SaaS data

Tools

Snowflake

BigQuery

Job description

Stuut is transforming how B2B companies turn revenue into cash. Businesses worldwide have trillions tied up in receivables, yet the work between order and payment still relies on fragmented systems and labor-intensive manual processes. Stuut’s AI agent works across order management, credit, collections, payments, cash application, disputes and deductions, carrying context through every step. Customers reduce DSO by 47%, collect 40% more cash and eliminate 70% of manual work without replacing their ERP.
Stuut is already trusted by finance teams at companies including Honeywell, NCR and ZoomInfo, from Fortune 10 enterprises to scaling mid-market businesses. We are backed by a16z, Khosla Ventures, Activant, 1984 Ventures, Page One and Microsoft.

The Role

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.

What You’ll Do

• 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

• Build the transformation and semantic layer that serves as the single source of metric truth across customer-facing analytics, internal reporting, and our AI/ML systems

• Design the canonical data model that normalizes information across heterogeneous source systems, with quality tests and observability built in from day one

• Build the event and signal pipelines that turn product interactions and outcomes into clean, labeled data — the foundation for analytics, ML, and intelligent product features

• Partner with product, engineering, and applied ML to embed data quality, lineage, and observability into everything we ship

• Implement DataOps best practices so our data — and the AI features built on top of it — stays timely, accurate, and trusted

• 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

You Might Be a Fit If You…

• Have 3+ years of hands-on experience building production data pipelines using Python

• Know your way around SQL and modern cloud data warehouses; experience with Snowflake or BigQuery is a plus

• Have deep experience implementing ETL/ELT workflows at scale using tools like dbt, Airflow, or similar — and have opinions on what good looks like

• Have built or contributed to a semantic / metrics layer and care about metric consistency across surfaces

• Understand data modeling fundamentals and can design canonical schemas that normalize messy, heterogeneous source data into something usable

• Have worked with real-world data from SaaS APIs, ERPs, and third-party integrations — and have battle scars to show for it

• Care deeply about data quality and observability — freshness, lineage, automated testing, and anomaly detection as first-class concerns

• Have experience partnering with ML or applied AI teams on feature pipelines or supporting data infrastructure (bonus, not required)

• Thrive in ambiguity and get energized by building something new rather than inheriting someone else's stack

• 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