Data Analyst, NYC

Stripe · New Yorksenior

In short

▸Analista de datos que construye infraestructura de datos para productos globales como Pricing Adaptativo y Managed Payments.
▸Día a día: crea modelos escalables, dashboards y pipelines de producción, con foco en mercados LATAM y EMEA.
▸Destacado: trabajas con datos fundamentales de Stripe que impactan directamente en el crecimiento global de la empresa.

Proficiency with AI tools to accelerate model development, analysis, and coding

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What they ask for

✓6+ años de experiencia en roles analíticos o de ingeniería de datos
✓Dominio avanzado de SQL con optimización de consultas
✓Habilidades en Scala o Python para desarrollo de pipelines
✓Experiencia con Spark y frameworks distribuidos
✓Uso de herramientas de orquestación como Airflow o Flyte
✓Experiencia comprobada en product pipelines de producción, con pruebas y documentación

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SQLScalaPythonSparkAirflowFlytedata modelingdashboardingautomated reportingAI tools

Who should you write to at Stripe?

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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 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. We have a variety of Data Analytics roles and teams across Stripe and Data Analysts are hired in line with the business needs and domain of the organization they will support. What you’ll do 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 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 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 • 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

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