{"id":744994,"url":"https://alion.io/job/stuut-data-engineer","title":"Data Engineer","company":{"id":687145,"name":"Stuut","domain":"stuut.ai","url":"https://alion.io/company/stuut","size_band":"51-200","is_staffing_agency":false,"employer_type":"direct","is_intermediary":false,"listed_via":null,"ats_vendor":"Ashby","truth_index":null},"role":"Data Science","role_family":"Data Science","seniority":"senior","employment_type":"full_time","work_mode":"on_site","remote_scope":null,"remote_scope_basis":null,"remote_working_hours":null,"hiring_geo_confidence":"structured","locations":["San Francisco, United States","New York, United States"],"countries":["US"],"hiring_countries":[],"hiring_countries_total":0,"salary":{"min":150000,"max":200000,"currency":"USD","period":"year","gross":null,"usd_annual":200000},"salary_estimate":null,"experience_years_min":5,"visa_sponsorship":false,"relocation_package":false,"has_equity":true,"technologies":[{"name":"Google BigQuery","optional":false},{"name":"Python","optional":false},{"name":"Snowflake","optional":false},{"name":"SQL","optional":false},{"name":"Anomaly Detection","optional":true},{"name":"dbt","optional":true},{"name":"ETL/ELT","optional":true}],"status":"live","first_seen_at":"2026-09-03T16:25:45Z","employer_posted_date":"2026-09-03","last_verified_at":"2026-11-02T15:32:36Z","board_verified":true,"closed_at":null,"days_open":60,"trust":{"level":"ok","repost_count":null,"flags":[],"days_open":60},"description":"About Stuut\nStuut is the AI coworker that runs order-to-cash for the world’s leading enterprises. Across order management, credit, collections, payments, cash application, disputes and deductions, Stuut does the work end to end and keeps going until the cash hits the bank.\nOver 150 companies, spanning the mid-market to the Fortune 50, including Honeywell, ZoomInfo and PerkinElmer, use Stuut to unlock up to 40% more cash flow and cut DSO by 47%. More than $3 billion has moved through the platform to date.\nFounded in New York by Tarek Alaruri and Ben Winter, Stuut has raised $93 million from Insight Partners, Andreessen Horowitz, M12, Microsoft’s Venture Fund, and others. Learn more at stuut.ai.\nThe Role\nTo 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.\nThis 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.\nWhat You’ll Do\nBuild 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\n\nBuild 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\n\nDesign the canonical data model that normalizes information across heterogeneous source systems, with quality tests and observability built in from day one\n\nBuild the event and signal pipelines that turn product interactions and outcomes into clean, labeled data - the foundation for analytics, ML, and intelligent product features\n\nPartner with product, engineering, and applied ML to embed data quality, lineage, and observability into everything we ship\n\nImplement DataOps best practices so our data - and the AI features built on top of it - stays timely, accurate, and trusted\n\nCollaborate with leadership to define KPIs, build dashboards, and surface insights that drive strategic decisions\n\nScale our data platform as we grow from dozens to hundreds of customers, anticipating needs before they become bottlenecks\n\nYou Might Be a Fit If You…\nHave 5+ years of hands-on experience building production data pipelines using Python\n\nKnow your way around SQL and modern cloud data warehouses; experience with Snowflake or BigQuery is a plus\n\nHave deep experience implementing ETL/ELT workflows at scale using tools like dbt, Airflow, or similar - and have opinions on what good looks like\n\nHave built or contributed to a semantic / metrics layer and care about metric consistency across surfaces\n\nUnderstand data modeling fundamentals and can design canonical schemas that normalize messy, heterogeneous source data into something usable\n\nHave worked with real-world data from SaaS APIs, ERPs, and third-party integrations - and have battle scars to show for it\n\nCare deeply about data quality and observability - freshness, lineage, automated testing, and anomaly detection as first-class concerns\n\nHave experience partnering with ML or applied AI teams on feature pipelines or supporting data infrastructure (bonus, not required)\n\nThrive in ambiguity and get energized by building something new rather than inheriting someone else's stack\n\nHave experience (or strong interest) in fintech, B2B SaaS, or financial data - understanding AR/AP workflows is a big plus\n\nUS Compensation\nTop-of-market salary and equity package\n\nBenefits (for U.S.-based full-time employees)\n\nMedical, dental & vision insurance coverage for you\n\n401(k) & Match\n\nEquity\n\nFlexible PTO\n\nParental Leave\n\nStuut is an equal opportunity employer committed to building a team with diverse backgrounds, perspectives, and experiences. We do not discriminate based on race, color, religion, sex, sexual orientation, gender identity or expression, national origin, age, disability, veteran status, genetic information, or any other characteristic protected by applicable law.\nWe are also committed to providing reasonable accommodations throughout the application and interview process. 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