About Us:
At Parafin, we’re on a mission to grow small businesses.
Small businesses are the backbone of our economy, but traditional banks often don’t have their backs. We build tech that makes it simple for small businesses to access the financial tools they need through the platforms they already sell on.
We partner with companies like DoorDash, Amazon, Worldpay, and Mindbody to offer fast and flexible funding, spend management, and savings tools to their small business users via a simple integration. Parafin takes on all the complexity of capital markets, underwriting, servicing, compliance, and customer service for our partners.
We’re a tight-knit team of innovators hailing from Stripe, Square, Plaid, Coinbase, Robinhood, CERN, and more — all united by a passion for building tools that help small businesses succeed. Parafin is backed by prominent venture capitalists including GIC, Notable Capital, Redpoint Ventures, Ribbit Capital, and Thrive Capital. Parafin is a Series C company, and we have raised more than $194M in equity and $340M in debt facilities.
Join us in creating a future where every small business has the financial tools they need.
About the Position
We are looking for a Data Analytics Engineer to build and scale the data models, pipelines, and analytics infrastructure that power decision-making across Parafin. You'll design reliable datasets, transform raw data into trusted business metrics, and partner closely with Product, Engineering, Finance, Risk, and Operations. You'll also leverage modern AI tools to accelerate development and help build scalable, efficient analytics workflows. Your work will enable teams across the company to make better decisions and help us build products that expand access to financial services for small businesses.
Are you a curious, analytical, and collaborative individual with a passion for turning large, complex datasets into actionable insights? If so, come join us!
What You’ll Be Doing:
Build and maintain scalable data pipelines that power analytics data models and trusted datasets.
Write efficient SQL to transform, validate, and optimize data for analytics and reporting.
Leverage AI tools to accelerate development, improve productivity, and streamline analytics workflows.
Develop and maintain dashboards, reports, and self-service analytics for business stakeholders.
Partner with Product, Engineering, Finance, Risk, and Operations to understand data needs and deliver data-driven solutions.
Monitor data quality, investigate discrepancies, and improve the reliability of our data.
Contribute to the continuous improvement of Parafin's analytics infrastructure and analytics engineering practices.
What We’re Searching For:
1–3 years of experience in Analytics Engineering, Data Analytics, Business Intelligence, Data Engineering, or a similar role.
Strong SQL skills.
Experience working with relational databases and data warehouses.
Experience with Python or another scripting language.
Familiarity with dbt or a desire to learn modern analytics engineering tools.
Experience building dashboards in Looker, Tableau, Sigma, Mode, or similar BI tools.
Strong analytical and problem-solving skills.
Excellent communication and collaboration skills.
Bachelor's degree in Computer Science, Statistics, Engineering, Mathematics, Economics, or a related quantitative field (or equivalent experience).
We Prefer If You Have:
Knowledge of data modeling and analytics engineering best practices.
Experience with Databricks, Snowflake, BigQuery, or other cloud data platforms.
Experience with Git and version control.
Familiarity with Airflow, Dagster, or other workflow orchestration tools.
Experience working with financial services, lending, payments, or product analytics data.
Experience in a startup or other fast-paced, high-growth environment.
What We Offer
Salary Range: $180k - $220k
Equity grant
Medical, dental & vision insurance
Unlimited PTO
Work from home flexibility
Commuter benefits
Free lunches
Paid parental leave
401(k)
Employee assistance program
If you require reasonable accommodation in completing this application, interviewing, completing any pre-employment testing, or otherwise participating in the employee selection process, please contact us.