Senior Staff Engineer, Big Data Infrastructure

<h2><strong>Who we are</strong></h2> <h3><strong>About Stripe</strong></h3> <p>Stripe is a financial infrastructure platform for businesses. Millions of companies - from the world’s largest enterprises to the most ambitious startups - use Stripe to accept payments, grow their revenue, and accelerate new business opportunities. Our mission is to increase the GDP of the internet, and we have a staggering amount of work ahead. That means you have an unprecedented opportunity to put the global economy within everyone’s reach while doing the most important work of your career.</p> <h3><strong>About the team</strong></h3> <p>In this role, you’d be joining the Big Data Infrastructure team. Our team builds and maintains the platforms that power data work across Stripe, managing three core layers:</p> <ul> <li>Data Orchestration (Airflow)</li> <li>Batch Compute (Spark, Celeborn)</li> <li>Data Lake (Iceberg, Hive, S3, Azure Blob Storage)</li> </ul> <p>We support over 2,000 engineers and 600+ internal teams, processing workloads that organically grow more than 30% year over year.&nbsp;Our infrastructure handles massive scale, managing over 800 PB of data, running 325,000 applications a day, and accounting for hundreds of millions of dollars in annual spend, directly powering critical pipelines like inbound payments, network reconciliation, and capital underwriting.</p> <h2><strong>What you’ll do</strong></h2> <p>As the technical leader for the Big Data Infrastructure organization, you will guide a 40+ person engineering team to scale our foundational data systems. You will partner closely with major internal customers like Data Foundations, Payins Engineering, and AI/ML Foundations to modernize our tech stack and execute Stripe's transition to the "Agentic Era" - building "invisible infrastructure" where AI agents operate data pipelines end-to-end.&nbsp;</p> <h3><strong>Responsibilities</strong></h3> <ul> <li>Serve as the technical leader for the Big Data Infrastructure organization, overseeing distributed systems that manage 20% of Stripe's total AWS spend</li> <li>Execute Stripe's transition to the "Agentic Era" by building invisible infrastructure that empowers AI agents to author, validate, ship, and operate data pipelines</li> <li>Drive the architecture and delivery of critical modernization bets, including YARN to Kubernetes migrations, native vectorization (Gluten/Velox), and Airflow and Data Catalog modernization</li> <li>Lead the implementation of a multi-region and multi-cloud data strategy for high availability, disaster recovery, and Azure Blob Storage compliance</li> <li>Reduce operational burden and maintenance overhead (KTLO) from over 40% to under 10% by shifting fixes into the platform instead of relying on runbooks</li> <li>Foster a culture of operational excellence and mentor engineers at various stages in their careers, up to Staff+</li> </ul> <h2><strong>Who you are</strong></h2> <p>We’re looking for someone who meets the minimum requirements to be considered for the role. If you meet these requirements, you are encouraged to apply. The preferred qualifications are a bonus, not a requirement.</p> <h3><strong>Minimum requirements</strong></h3> <ul> <li>BS or MS in Computer Science or a related field</li> <li>This is a Senior Staff role, so ideally 12+ years of professional experience in a software development role</li> <li>A strong engineering background in distributed infrastructure and/or platform services, including one or more of the following: storage, databases, or compute</li> <li>Experience leading projects on a cross-team and company-wide scale, including scaling and migrating systems with little to no downtime</li> <li>Experience developing, maintaining, and debugging distributed systems while optimizing their reliability and security</li> <li>Experience driving a culture of operational excellence, with a deep understanding of metrics, alerts, and dashboards</li> </ul> <h3><strong>Preferred qualifications</strong></h3> <ul> <li>Experience driving AI-led architectural transformations and integrating agentic workflows into large-scale data systems</li> <li>Experience in a development team at AWS, Azure, OCI, or Google</li> <li>Experience with big data infrastructure at scale, such as Spark, Iceberg, S3, Airflow, YARN, and Celeborn</li> <li>Experience with database internals and/or with Kubernetes</li> </ul>