Software Engineer, Growth Data Engineering

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
Stripe is the best software platform for running an internet business.
We handle billions of dollars every year for hundreds of thousands of
businesses around the world. One third of Americans bought something on
Stripe in the last year.
With all this data, the Growth Data Engineering team is looking for
talented data-minded engineers to help us manage business critical data
leveraged across the entire organization. If you are passionate about
data, excited about designing data pipelines and data-driven user
experiences, and motivated by having an outsized impact on the business,
we want to hear from you.
What you’ll do
Every record in our data warehouse is vitally important for the
businesses that use Stripe, so we’re looking for people with a strong
background in data engineering and analytics to help us scale while
maintaining correct and complete data. You’ll be working with a variety
of internal teams across Growth, Sales, Marketing, and Data Science to
help them solve their data needs. Your work will provide teams with
visibility into how Stripe’s Growth organization is performing and how
we can deliver a better experience to Stripe's customers.
Responsibilities

• Design and build client libraries and frameworks to log events and accurately track the behavior of users interacting with our logged-out user interfaces such as Stripe.com
• Identify data needs for Growth, Sales, and Marketing teams, understand their specific operational and reporting requirements, and build efficient and scalable data products & pipelines to enable data-driven decisions across Stripe
• Build data pipelines that track key GTM product metrics, and measure the impact of different GTM strategies employed by teams in the field
• Build Stripe's Customer Engagement Data Service - collecting, curating, mastering, enriching, and presenting a single view of user interactions with Stripe for consumption by data applications across the company
• Help the Data Science team apply and generalize statistical and econometric models on large datasets to empower more intelligent decision making among our Growth & Go-to-Market teams
• Integrate different parts of our experimentation infrastructure at Stripe, to enable full-funnel measurement and personalization of experiences spanning from Stripe.com into product
• Develop strong subject matter expertise and manage the SLAs for both data pipelines and full stack web applications that support the Growth & Go-to-Market organizations at Stripe
• Refine our existing data marts that help the Sales and Marketing organization at Stripe forecast the future potential performance of the business, and reliably measure their ongoing attainment toward targets
• Build and refine Stripe's data foundations - infrastructure, pipelines, and tools to enable Growth, Sales, and Marketing teams at Stripe - working with Scala, Spark, and Airflow
• Our stack spans tools in Spark, Scala, Python, Spark, SQL, Presto, Airflow, AWS, Java, Go, and React
• Design, develop, and own data pipelines, models, and products that power Stripe’s Growth, Sales, and Marketing teams

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

• An inquisitive nature in diving into data inconsistencies to pinpoint issues, and resolve deep rooted data quality issues
• Prior experience with writing and debugging data pipelines using a distributed data framework (Spark / Hadoop / Pig etc)
• A strong engineering background and are interested in data
• Experience with full stack development languages such as Java or Go, and front-end frameworks such as React
• Knowledge of a scientific computing language (such as Scala or Python) and SQL
• The ability to communicate cross-functionally, derive requirements and architect shared datasets
• 3+ years of experience in a Data Engineering or Software Engineering role, with a focus on building data pipelines, or applications powered by big data.