Full Stack Engineer - San Francisco, United States - Stripe

Stripe San Francisco, United States

1 week ago

Description

Who we are

About Stripe

Stripe is a financial infrastructure platform for businesses. Millions of companies—from the world's largest enterprises to the most ambitious startups—use Stripe to accept payments, grow their revenue, and accelerate new business opportunities. Our mission is to increase the GDP of the internet, and we have a staggering amount of work ahead. That means you have an unprecedented opportunity to put the global economy within everyone's reach while doing the most important work of your career.

About the team

Our Revenue and Finance Automation (RFA) suite gives businesses power over the entire life cycle of their cash flow. By coordinating billing, tax, reporting, and data services in one modern stack, Stripe's RFA suite eliminates the inefficiencies of legacy finance tools and supports revenue growth.

Our portfolio is growing rapidly and we are expanding our RFA suite to serve the diverse spectrum of Stripe's users, from brand new startups to public companies. Simultaneously we are investing in foundations for an extensible platform solution, including integrations with external systems that will let us scale our reach and capabilities by orders of magnitude over the next few years.

As part of the RFA Growth Engineering team, you will build and own the systems, products, internal tools, and customer-facing experiences that power intelligence behind our go-to-market and product-led growth. This includes building our ML powered recommendations and growth experimentation engine(s), multi-channel notifications systems, and key growth-related customer experiences (e.g., onboarding experiences, user dashboards, product recommendations).

What you'll do

We're looking for an experienced Full Stack Engineer to join our team and lead initiatives focused on accelerating the growth of Stripe's Revenue and Finance Automation suite. In this role, you will be responsible for defining and implementing data-driven strategies to improve user acquisition, adoption, and retention across many of Stripe's user-facing surfaces. You will help foster a culture of experimentation and data-driven decision making, and define best practices that enable the team to iterate and learn in increasingly tight feedback loops. You will excel in this role if you're a growth-focused full stack engineer who can collaborate effectively across multiple teams and functions to deliver results.

Responsibilities

Design and implement experiments across Stripe products, including the Stripe dashboard, hosted surfaces, and docs.
Partner closely with engineering, product, and design leadership to define and implement our growth and experimentation strategy.
Foster a culture of experimentation and data-driven decision making on the team and the broader organization.
Build a deep understanding of our data, and identify opportunities to track additional metrics or build new data pipelines to further operationalize growth.
Work in a variety of languages and technologies, including Ruby, Java, Typescript, React, and GraphQL

Who you are

We're looking for someone who meets the minimum requirements to be considered for the role. If you meet these requirements, you are encouraged to apply. The preferred qualifications are a bonus, not a requirement.

Minimum requirements

3+ years of experience as in full time software development roles.
An understanding of A/B testing techniques and experimentation methodologies.
You can work effectively across the stack from top to bottom, comfortably navigating codebases with different languages and tools.
You're equally as comfortable shipping user-facing experiences as you are writing custom queries to analyze experiment results.

Preferred qualifications

You're self-directed and can operate autonomously across multiple teams to deliver scaled impact.
5+ years of experience in full time software development roles
2+ years of experience working in a growth-focused role or team.
Experience with machine learning, recommender systems, product-led growth, and/or lifecycle marketing.

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