Data Analyst, NYC

at Stripe

USD 161,600-242,400 per year

SENIOR

✅ On-site

Tech Stack
Tag name is followed by "@" symbol and proficiency level value. About proficiency levels:

1-2 — basic awareness. Minimal hands-on experience, and a rudimentary understanding of the technology's purpose;

3-6 — daily use. Comfortable and regular usage, capable of handling common tasks and challenges related to the technology;

7-9 — you are an expert, you can teach others, you know all the pitfalls and tricks;

10 — exceptional knowledge, comprehensive understanding, and adeptness in all aspects of the technology, including advanced problem-solving. Think twice before claiming or demanding such level.

AI @ 6 Airflow @ 4 BI Data Engineering @ 7 Data Modeling @ 6 Data Pipelines @ 4 Data Science Payments Python @ 6 SQL @ 6 Scala @ 6 Spark @ 4

Details

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. Stripe’s mission is to increase the GDP of the internet.

About the Team

Data Science at Stripe is a vibrant community where data analysts and data scientists learn and grow together. You’ll work with some of the most fundamental data at Stripe and use that data to help drive company-wide initiatives. Stripe has a variety of Data Analytics roles and teams, and Data Analysts are hired in line with the business needs and domain of the organization they support.

Role Description

We’re looking for a Data Analyst to partner with Stripe’s Global organization, helping millions of users sell around the world. You’ll help build analytics and data products for solutions such as Adaptive Pricing and Stripe Managed Payments, as well as Stripe’s expansion into new markets across LATAM and EMEA.

Responsibilities

Design and build scalable data models and infrastructure to power product analytics and metrics reporting as new products launch and grow.
Own business-critical data products, including Tier-1 datasets and production pipelines, ensuring reliability through rigorous testing, monitoring, and documentation.
Build and maintain metric definitions, metadata, and business context that enable AI agents to help stakeholders explore trusted data and answer business questions independently.
Develop dashboards, automated reporting, and thoughtful analyses to surface actionable insights and proactively identify business opportunities.
Partner closely with senior business leaders to translate business needs into analytical questions and deliver clear recommendations through deep-dive analyses.
Shape product and business strategy across global markets by distilling complex findings into compelling data narratives for senior stakeholders.

Requirements

At least 6 years of full-time experience in Data Engineering, Analytics Engineering, Business Intelligence Engineering, or a related analytical role.
Proficiency in SQL, including complex query optimization and data modeling.
Proficiency in Scala or Python for data pipeline development, not just scripting and SQL.
Experience with distributed data frameworks such as Spark to write and debug data pipelines.
Experience with workflow orchestration tools such as Airflow, Flyte, or equivalent.
Proven ability to design, implement, and maintain production-grade data pipelines and dashboards.
Good understanding of development processes and best practices, including engineering standards, code reviews, and testing.
Ability to clearly communicate results and drive impact with cross-functional partners.
Experience owning production data products with defined quality standards, testing, and documentation.
Proficiency with AI tools to accelerate model development, analysis, and coding.