Data Analyst, Financial Data Engineering

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.

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

Requirements

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