Role Description & Responsibilities
Data Analytics
About Stripe
Stripe is a high-growth technology leader building scalable solutions for global users. Millions of companies and teams rely on their infrastructure and services to execute high-value workflows, analyze massive datasets, and scale modern operations.
CadetX Candidate Advantage: As an applicant for this Data Analytics role, you are evaluated on practical proficiency with real-world query execution, data pipelines, and clear stakeholder communication.
CadetX Role Brief & Company Specifications
Role Mission & Impact
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.
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.
Key Responsibilities & Day-to-Day Scope
- ✓ 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
- ✓ 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
Official Qualifications & Technical Requirements
- • 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
Preferred Skills & Technology Stack
- + Experience working with cloud data warehouses (Snowflake, BigQuery, or Amazon Redshift).
- + Familiarity with Git version control and collaborative code review workflows.
- + Demonstrated portfolio or capstone projects exhibiting practical end-to-end analytics problem solving.
Tech Stack & Tools in this role
Expected technical competencies for Day 1 productivity:
★ Life & Culture at Stripe
Verified EmployerStripe champions rigorous analytical discipline, continuous learning, and low-ego teamwork. Team members enjoy flexible hybrid allowances, learning stipends, and structured mentorship to fast-track career mobility.