Strategic Overview
Data Analyst, NYC at Stripe is a data opportunity centered on the specialist responsibilities and outcomes described in the employer's listing.
The published role emphasizes work such as 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….
The role is listed for New York with the working arrangement published with the role, giving candidates the practical context needed to assess fit before applying.
Key information at a glance
About This Role
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 & Objectives
- 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
Required Qualifications & Candidate Blueprint
- 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
Salary & Benefits
The available source data does not publish a numerical salary range for this opening. We do not estimate or substitute third-party figures.
Full Job Description
The following is the complete job description supplied by the source. We sanitize unsafe markup and remove external links, but do not shorten or rewrite the employer's source content.
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
Editor’s Market Perspective (Our Custom Analysis)
Why This Position Matters
This data opening is a useful opportunity for candidates whose experience matches the role-specific capabilities named in the listing. Its strongest career signal is the scope of the work itself — particularly Design and build scalable data models and infrastructure to power product analytics and metrics reporting as we launch and grow new products — rather than a generic title alone.
Resume & Application Strategy
For the application, mirror the employer's language where it truthfully matches your background: foreground the role-specific capabilities named in the listing, quantify outcomes from comparable work, and place the most relevant experience near the top of the resume. If the listing specifies tools, platforms, leadership scope, or domain experience, use those exact terms in context instead of presenting an unrelated keyword list.
We organize source-provided information into this independent job-seeker overview. Compensation is shown only when the source provides it; the official listing remains the authority for current requirements and application instructions.