Staff Software Engineer, Business Data & Data Pipelines

EngineersOfAI; Seattle (WA); On-site; USD 180,000 - 240,000; Full time

Job summary

Stripe is seeking a Staff-level data engineering leader to drive high-impact data pipelines and analytics across finance, product, and go-to-market teams. You will mentor engineers, shape data platforms, and partner with cross-functional teams to deliver trusted datasets and scalable warehouses.

The role emphasizes leadership, deep data engineering expertise, and collaboration with Stripe teams to unlock new capabilities using AI and large language models.

Qualifications

• This is a Staff-level role — typically 10+ years building and operating data systems, pipelines, warehouses, and leading teams.

Responsibilities

• Lead the technical outcomes for a team of engineers, providing mentorship and guidance.
• Partner with recruiting to attract and hire top talent.
• Deliver cutting-edge data pipelines that scale to users’ needs, focusing on reliability and efficiency.
• Develop subject matter expertise and manage SLAs of data pipelines and web applications.
• Collaborate with product managers to create canonical datasets and data warehouses.
• Leverage AI/LLM and Agents at scale to analyze high-quality data on ambiguous problems.
• Drive key data initiatives from planning to delivery with high quality and timely completion.
• Foster a collaborative, inclusive environment promoting innovation and knowledge sharing.

Skills

Data pipelines

Leadership

SQL

Backend development

Tools

Airflow

Spark

Kafka

Flink

Job description

Stripe is seeking a Staff-level data engineering leader to drive high-impact data pipelines and analytics across finance, product, and go-to-market teams. You will mentor engineers, shape data platforms, and partner with cross-functional teams to deliver trusted datasets and scalable warehouses.

The role emphasizes leadership, deep data engineering expertise, and collaboration with Stripe teams to unlock new capabilities using AI and large language models.