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CoE Data & Insights

Stripe

Greenhouse
OnsiteBengaluruabout 11 hours ago
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Job 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

The Customer Success (CS) team at Stripe supports revenue growth across GTM by helping a broad book of users activate, grow, and maximize their performance on Stripe.

This team, part of the Customer Success Organization, leads the charge in using data to inform strategic decisions and enhance operations across the company. We excel in pinpointing new opportunities, optimizing processes, and executing impactful projects at the team level. By crafting reusable data products and upholding high data standards, we deliver consistent and excellent results. Our role requires close collaboration with cross-functional partners to develop sustainable metrics and data models with long-term value. Combining payment expertise with technical skills, we manage data pipelines and maintain key analytics assets, simplifying complex technical concepts for diverse stakeholders.

What you'll do

In this role, you'll spearhead innovation by identifying transformative opportunities and developing scalable data solutions. You'll optimize data infrastructure and align initiatives with strategic goals, fostering collaboration across teams. By promoting a data-driven culture and building strong partnerships, you'll ensure sustainable growth and informed decision-making throughout the Customer Success and Paid Support Organization.

You're also instrumental in building datasets and tools that enable externally facing Stripe employees to deliver tailored content to their customers.

Responsibilities

  • Identify and scope new opportunities, processes, and projects that have team-level impact
  • Create reusable data products (dashboards, data models, code) that set high standards for future projects and for other analysts across the organization
  • Assist in developing the team's data pipelines and performance workbooks by leveraging both your expertise in payments and technical skills. This involves building metrics pipelines, writing code, and being proficient with SQL
  • Set priorities for the Customer Success team's technical and data opportunities, secure partner buy-in, and manage reprioritization as needed
  • Develop vertical agents that solve the Customer Success teams' most manual or repetitive tasks
  • Maintain analytics assets owned by the team, such as metric definitions, technical documentation, query libraries, and other tooling
  • Act as a resource to the team and broader business on the technical complexity of Customer Success datasets, communicating concepts clearly to cross-functional partners and stakeholders

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

  • 3–8+ years of experience in Data Analysis, Business Intelligence Engineering, or Technical Customer Advisory roles
  • Expertise in data visualization and using data insights to make recommendations
  • Comfortable collaborating across functions to identify data analytics problems and execute solutions with technical rigor and data-driven insights
  • Familiarity with card payments ecosystem
  • Proven ability to manage multiple projects, communicate results clearly to diverse stakeholders, and drive business outcomes independently in a fast-moving environment

Preferred qualifications

  • Proficiency in SQL (advanced), Python, and git (intermediate)
  • Data visualization, dashboard building, modeling, and reporting automation