Data Analyst, Financial Data Engineering
Stripe•3h ago
United StatesOnsiteFull-timeMid Level6+ yrs exp
H-1B sponsor
Top focus
Data AnalystFinancial AnalystVp EngineeringVp DataData Engineer
- 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
- accelerate new business opportunities. Our mission is to increase the GDP of the internet
- 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
- 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
- In this role, you'll partner deeply with teams across Stripe to ensure that our users, our products
- our business have the models, data products
- insights needed to make decisions and grow responsibly. You'll design, build
- own the scalable data infrastructure that powers analytics and reporting across the company.
- Day to day, you'll translate complex business requirements into reliable data models, own end-to-end pipeline development from raw data ingestion to clean, consumption-ready datasets
- work with leaders to prioritize the highest-impact data investments. You'll go beyond building dashboards—you'll architect the data layer that makes self-service analytics possible and deliver actionable business recommendations through rigorous analysis and data storytelling.
- Responsibilities
- Design, build, and maintain scalable data pipelines and ETL/ELT workflows that power production-grade financial reporting, risk measurement, and operational decisioning for Treasury Finance
- Leverage AI tools (code assistants, LLM-based agents) to accelerate pipeline development, data quality automation, reconciliation, and documentation - expanding technical scope while maintaining quality.
- Model and transform raw data into clean, well-documented datasets that serve as the core foundations for decision making for Treasury Finance (e.g. float positions, cash explainability, risk exposures, liquidity management)
- Establish and enforce data quality standards through testing, monitoring, and alerting on pipeline health
- Establish and own data freshness SLAs, operational alerting, and incident response for your data domains - ensuring production reliability for risk and finance critical workflows
- Partner deeply with Treasury Finance, data scientists/analysts, and engineers to define data requirements and deliver trusted, reusable financial data products
- Partner deeply with Treasury Finance stakeholders to translate business requirements into data architecture decisions, anticipating needs and helping to drive data strategy rather than reacting to requests
- Build self-service tooling and analytics layer that empower stakeholders to access and explore trusted data autonomously
- 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 Python for data pipeline development, not just scripting
- 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
- Preferred qualifications
- Prior experience at a growth-stage internet or software company
- Prior experience working with Finance or Treasury teams
- Understanding of treasury and finance concepts (e.g., float positions, FX exposure, cash reconciliation, balance sheet usage, liquidity management)
- Experience with data quality frameworks, data contracts, tiering/classification, or SLA management
- Experience creating leadership-level reporting, such as QBRs and MBRs
- Experience building financial reporting infrastructure - e.g. automated treasury processes, regulatory reporting, or finance close
- Proficiency with AI tools (code assistants, LLM agents) to accelerate pipeline development and data quality automation
- Interest in how data products enable automated/agentic workflows — understanding that data quality determines the reliability of every downstream decision
Required skills
SQLPythonSparkAirflow