What you'll doWe'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 we launch and grow new products
- Own business-critical data products, including Tier-1 datasets and production pipelines, ensuring reliability through rigorous testing, monitoring, and documentation
- Build and maintain the 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
Who you areWe'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- 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 like Spark to write and debug data pipelines
- Experience with workflow orchestration tools (e.g. 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 like 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
