Data Engineer, Treasury Finance Analytics & Pipelines

Nubeero Limited; New York (NY); On-site; USD 120,000 - 180,000; Full time

Job summary

Stripe is seeking a Data Engineer to design, build, and own scalable data infrastructure powering analytics and reporting across the company. You will translate complex business needs into reliable data models and end-to-end data pipelines for Finance and Treasury operations.

Join a dynamic Data Science group that drives actionable insights, data storytelling, and self-serve analytics through robust data foundations and dashboards.

Qualifications

• 6+ years of data engineering or analytics engineering experience.
• Proficiency in SQL with complex queries and data modeling.
• Python for data pipeline development, beyond scripting.

Responsibilities

• Design, build, and maintain scalable data pipelines and ETL/ELT workflows for production-grade financial reporting and risk measurement.
• Leverage AI tools to accelerate pipeline development, data quality automation, and documentation.
• Model and transform raw data into clean, well-documented datasets for decision making in Treasury Finance.
• Establish and enforce data quality standards with testing, monitoring, and alerts.
• Own data freshness SLAs and incident response for data domains ensuring production reliability.
• Collaborate with Treasury Finance, data scientists, analysts, and engineers to define data requirements and deliver trusted data products.
• Translate business requirements into data architecture decisions and drive data strategy.

Skills

SQL

Python

Data pipelines

Data modeling

Communication

Distributed frameworks

Tools

Spark

Airflow

Flyte

Job description

Stripe is seeking a Data Engineer to design, build, and own scalable data infrastructure powering analytics and reporting across the company. You will translate complex business needs into reliable data models and end-to-end data pipelines for Finance and Treasury operations.

Join a dynamic Data Science group that drives actionable insights, data storytelling, and self-serve analytics through robust data foundations and dashboards.