Engineering Manager, Data Orchestration Platform

Stripe is a financial infrastructure platform for businesses, aiming to increase the GDP of the internet. They are seeking an Engineering Manager for their Data Orchestration Platform to lead a team responsible for the Airflow data workflow scheduling platform, ensuring its reliability and guiding architectural decisions.

Responsibilities:

• Own the Platform Roadmap: Define the multi-year direction for Airflow at Stripe — synthesizing the needs of a large and diverse set of consuming teams, resolving cross-team dependencies, and driving adoption of the next-generation platform across the organization
• Lead and Scale: Build, mentor, and grow a high-performing team, investing in career development and fostering a culture of operational excellence
• Ensure Operational Rigor: Maintain unwavering reliability for a Tier-0 platform that a significant portion of Stripe's daily data workloads depend on
• Technical Stewardship: Guide the team through high-stakes architectural decisions in workflow scheduling, containerized job execution, DAG lifecycle management, and large-scale platform migrations — setting the technical bar for reliability, developer experience, and systems design

Requirements:

• 10+ years of professional software development and engineering experience
• 5+ years of direct engineering management experience, successfully building and operating high-velocity technical teams
• Proven track record of driving significant infrastructure efficiency, managing capacity planning, and making data-driven cost-performance trade-offs
• Experience working effectively in highly cross-functional, global organizations
• Experience managing remote or geographically distributed engineering teams
• Technical background in building, scaling, and maintaining large-scale distributed data systems or Tier-0 infrastructure using open-source tools (e.g., Hadoop, Spark, Celeborn, Airflow, Kafka)
• Familiarity with managing a massive fleet of Linux servers, on-premise Hadoop clusters, and modern cloud data architectures (e.g., AWS S3, Graviton)
• Demonstrated ability to navigate strategic ambiguity and deliver complex, multi-quarter infrastructural projects from inception to completion
• Deep empathy for internal data users with a passion for building robust developer tooling and abstractions