Описание

Stripe is hiring a Data Analyst in New York City to build analytics and data products for global business initiatives. The role involves designing scalable data models, owning production data pipelines and Tier-1 datasets, and developing dashboards and analyses.

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

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