271K–407K USD / year
Senior Staff Engineer, Big Data Infrastructure
DataHybrid — New York, Seattle, South San Francisco, US
Published on 2026-11-05
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About this role
Lead technical direction for Stripe’s large-scale Big Data Infrastructure organization. Guide modernization and reliability work across systems supporting data orchestration, batch compute, and data lakes, while enabling AI agents to operate data pipelines.
About the company
Stripe provides payment infrastructure and financial tools that help businesses accept payments, manage subscriptions, and move money globally. It serves startups through large enterprises with APIs for online and in-person commerce.
The team
Big Data Infrastructure team within Infrastructure & Corporate Tech; partners with Data Foundations, Payins Engineering, and AI/ML Foundations.
Stack
AirflowSparkCelebornIcebergHiveAmazon S3Azure Blob StorageYARN
What you'll do
- Set technical direction for the Big Data Infrastructure organization and its distributed systems.
- Build platform capabilities for AI agents to author, validate, ship, and operate data pipelines.
- Lead YARN-to-Kubernetes migration, native vectorization, and Airflow and Data Catalog modernization.
- Implement multi-region and multi-cloud strategies for availability, disaster recovery, and compliance.
- Reduce operational maintenance work by moving fixes into the platform.
- Promote operational excellence and mentor engineers through Staff+ levels.
What we're looking for
- BS or MS in Computer Science or a related field.
- Ideally 12+ years of professional software development experience.
- Strong background in distributed infrastructure or platform services, such as storage, databases, or compute.
- Experience leading cross-team, company-wide projects and low-downtime system migrations.
- Experience developing and debugging distributed systems with a focus on reliability and security.
- Experience driving operational excellence using metrics, alerts, and dashboards.
Nice to have
- Experience with AI-led architecture transformations or agentic workflows in large-scale data systems.
- Experience at AWS, Azure, OCI, or Google.
- Experience with large-scale big data infrastructure, including Spark, Iceberg, S3, Airflow, YARN, or Celeborn.
- Database internals or Kubernetes experience.
Benefits
- Equity
- Company bonus
- 401(k) plan
- Medical, dental, and vision benefits
- Wellness stipends