Data Engineer

OfferGenie; San Francisco (CA); Hybrid; USD 150,000 - 210,000; Full time

Benefits offered by this job

Equity

Health benefits

401(k)

Flexible PTO

Parental Leave

Job summary

OfferGenie is seeking its first data hire to build the data foundation powering the company’s analytics and AI features. You’ll design data architecture, pipelines, and models from scratch to transform raw financial data into actionable insights.

You’ll collaborate with product and engineering, own the canonical data model, and embed data quality and observability across everything shipped. This is a high-impact role with strategic influence.

Qualifications

• 3+ years of hands-on experience building production data pipelines with Python.
• Strong SQL skills and cloud data warehouses experience (Snowflake/BigQuery preferred).
• Experience implementing ETL/ELT workflows at scale with dbt, Airflow, or equivalents.
• Experience building a semantic/metrics layer with consistent metrics across surfaces.
• Solid data modeling fundamentals to normalize messy data into canonical schemas.
• Experience with SaaS APIs, ERPs, and third-party data integrations.
• Commitment to data quality, observability, lineage, testing, and anomaly detection.
• Bonus: collaboration with ML or applied AI teams on feature pipelines.

Responsibilities

• Build and own data infrastructure from the ground up, ingesting and modeling data from ERPs and payment systems.
• Create a canonical data model with tests and observability from day one.
• Develop event and signal pipelines turning product interactions into labeled data for analytics and ML.
• Partner with product, engineering, and ML teams to embed data quality in deliveries.
• Implement DataOps practices to keep data timely, accurate, and trusted.
• Define KPIs, build dashboards, and surface insights to drive strategic decisions.
• Scale the data platform as customer base grows, anticipating bottlenecks early.

Skills

Python

SQL

Data Warehousing

ETL/ELT

Data Modeling

Observability

Analytics

SaaS APIs

Fintech domain

Tools

dbt

Airflow

Snowflake

BigQuery

Job description

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