Data Software Engineer, Support Data Foundations

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.

The Support Experience organization builds and improves Stripe’s user support from end to end: how users get help within our products, how they get in touch with us when they have questions, and how our teams use internal tools to answer those questions. We’re accountable for the quality and reliability of this support stack and we use data and firsthand user research to continuously improve it. 

The Support Data Foundations team is looking for talented data-minded software engineers to help us manage business critical data leveraged across the entire organization.

Providing great support to our users is culturally important to everyone at Stripe. Our group consists of capable, friendly, user-oriented engineers that partner closely on this problem with Stripe’s world-class design, product, and operational teams. This includes the external-facing support interfaces (support.stripe.com), content, entry points, internal tooling, case routing, and helping teams across the company understand what’s causing users to contact support so that we can improve those experiences.

If you are passionate about designing data pipelines and building data-driven user experiences, and are motivated by our goal to build an industry leading, world class support experience, we want to hear from you.

You’ll help build and maintain fundamental building blocks for operational and support data insights. Many parts of the company leverage and build on top of our work to improve Stripe’s support offerings, including engineering, product, operations, data science, and more. Stripe provides many products with limitless usage patterns, creating a high degree of scale and complexity for users around the world. We’re looking for people with a strong background in data engineering and analytics to help us scale while maintaining correct and complete data. 

• Identify data needs for operations, product, and tooling teams to understand their specific operational and reporting requirements for support and support related areas
• Design, develop, and own efficient and scalable data products & pipelines to enable data-driven decisions across Stripe
• Help data science & ML teams apply and generalize statistical models on large datasets to empower more intelligent decision making
• Build and refine Stripe's data foundations - infrastructure, pipelines, and tools to enable stakeholders working with Scala, Spark, and Airflow
• Design and build client libraries and frameworks to log events and accurately track important usage and behavior information
• Build data pipelines that track key operations & product support metrics to help measure the impact of different strategies employed by operations teams
• Integrate with experimentation infrastructure at Stripe, to enable full-funnel measurement and personalization of experiences for users and support staff
• Help influence, create, and maintain best practices and data standards for tooling, querying, and reporting (including correctness, consistency, privacy, and timeliness)
• Our tech stack primarily spans Spark, Scala, Python, SQL, Presto, Airflow, MongoDB, AWS, Java, Go, Ruby, and React 

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.

• 5+ years of experience in a Data Engineering or Software Engineering role, with a focus on building data pipelines or applications powered by big data
• A strong engineering background and high interest in data
• Prior experience writing and debugging data pipelines using a distributed data framework (Spark, Hadoop, Pig, etc.)
• An inquisitive nature for diving into data inconsistencies to pinpoint issues, and resolve data quality issues regardless of the cause
• Proficiency with a scientific computing language (such as Scala or Python) and SQL
• The ability to clearly and effectively communicate cross-functionally, derive requirements and architect shared datasets
• A passion for supporting both external users and internal customers
• Have a high quality bar, attention to detail, and you help your team deliver polished products

• The ability to thrive with a high level of autonomy and responsibility
• Familiarity with Artificial Intelligence, Large Language Models (LLMs), or generative AI
• Experience working with operations or support teams
• Experience developing data intensive applications
• Experience leading a team of or mentoring other data and software engineers
• Experience developing, participating, or influencing team or company data strategy
• Experience and familiarity with any or all of the technologies mentioned above
• Experience with full stack development languages such as Ruby, Java, or Go, and front-end frameworks such as React