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Senior Staff Engineer, Big Data Infrastructure

Pay
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Work setting
Not stated
Employment
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What you’ll work on

Full posting
  • Lead the Big Data Infrastructure organization and guide a 40+ person engineering team

  • Drive architecture and delivery of YARN to Kubernetes and Airflow modernization projects

  • Build infrastructure that lets AI agents author, validate, ship, and operate data pipelines

  • Lead a multi-region and multi-cloud data strategy for availability and disaster recovery

  • Cut operational maintenance (KTLO) from over 40% to under 10% by fixing issues in the platform

From the employer’s posting
guide a 40+ person engineering team
Drive the architecture and delivery of critical modernization bets, including YARN to Kubernetes migrations
building invisible infrastructure that empowers AI agents to author, validate, ship, and operate data pipelines
Lead the implementation of a multi-region and multi-cloud data strategy for high availability, disaster recovery
Reduce operational burden and maintenance overhead (KTLO) from over 40% to under 10%

What you’ll bring

All qualifications

Core experience

  • Experience leading projects on a cross-team and company-wide scale, including scaling and migrating systems with little to no downtime
  • Experience developing, maintaining, and debugging distributed systems while optimizing their reliability and security
  • Experience driving a culture of operational excellence, with a deep understanding of metrics, alerts, and dashboards

Preferred experience

  • Experience driving AI-led architectural transformations and integrating agentic workflows into large-scale data systems
  • Experience in a development team at AWS, Azure, OCI, or Google
  • Experience with big data infrastructure at scale, such as Spark, Iceberg, S3, Airflow, YARN, and Celeborn
  • Experience with database internals and/or with Kubernetes
Qualification wording
Experience leading projects on a cross-team and company-wide scale, including scaling and migrating systems with little to no downtime
Experience developing, maintaining, and debugging distributed systems while optimizing their reliability and security
Experience driving a culture of operational excellence, with a deep understanding of metrics, alerts, and dashboards
Experience driving AI-led architectural transformations and integrating agentic workflows into large-scale data systems
Experience in a development team at AWS, Azure, OCI, or Google
Experience with big data infrastructure at scale, such as Spark, Iceberg, S3, Airflow, YARN, and Celeborn
Experience with database internals and/or with Kubernetes

About Stripe

Our mission is to increase the GDP of the internet, and we have a staggering amount of work ahead.

In the employer’s words · Read in context

Apply at Stripe

Posting record

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Actively hiringFirst seen by us 10 days ago, still listed, and not a repost of an earlier posting.

Status in our records
Live
First seen by us
Nov 5, 202610 days ago
Recorded sightings
6
Last seen by us
Nov 14, 2026

These dates show when we found the posting. Check the employer’s website to confirm it is still accepting applications.

How this job compares

Time since we first saw it

Day 10

Similar jobs usually come down between day 8 and day 57.

At Stripe, jobs usually come down by about day 60.

From 9,519 similar postings that came down, and 46 of Stripe’s. Coming down is not always a hire.

Stripe is hiring

35 open jobs

Open jobs by the week we first saw them, last 12 weeks.

  • Hiring is picking up
  • Takes jobs down at a usual pace
Hiring record

See how this role fits your experience

Add your resume and we’ll mark which of these tools you already use, and point out anything in the posting that could rule you out.

  • AWS
  • Azure
  • Hive
  • Iceberg
  • Kubernetes
  • S3
  • Spark
  • Airflow
Where the posting names them
Responsibilities - Serve as the technical leader for the Big Data Infrastructure organization, overseeing distributed systems that manage 20% of Stripe's total AWS spend - Execute Stripe's transition to the "Agentic Era" by building invisible infrastructure that empowers AI agents to author, validate, ship, and operate data pipelines
- Experience driving AI-led architectural transformations and integrating agentic workflows into large-scale data systems - Experience in a development team at AWS, Azure, OCI, or Google - Experience with big data infrastructure at scale, such as Spark, Iceberg, S3, Airflow, YARN, and Celeborn
- Batch Compute (Spark, Celeborn) - Data Lake (Iceberg, Hive, S3, Azure Blob Storage) We support over 2,000 engineers and 600+ internal teams, processing workloads that organically grow more than 30% year over year. 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.
- Drive the architecture and delivery of critical modernization bets, including YARN to Kubernetes migrations, native vectorization (Gluten/Velox), and Airflow and Data Catalog modernization - Lead the implementation of a multi-region and multi-cloud data strategy for high availability, disaster recovery, and Azure Blob Storage compliance - Reduce operational burden and maintenance overhead (KTLO) from over 40% to under 10% by shifting fixes into the platform instead of relying on runbooks
- Experience in a development team at AWS, Azure, OCI, or Google - Experience with big data infrastructure at scale, such as Spark, Iceberg, S3, Airflow, YARN, and Celeborn - Experience with database internals and/or with Kubernetes
- Execute Stripe's transition to the "Agentic Era" by building invisible infrastructure that empowers AI agents to author, validate, ship, and operate data pipelines - Drive the architecture and delivery of critical modernization bets, including YARN to Kubernetes migrations, native vectorization (Gluten/Velox), and Airflow and Data Catalog modernization - Lead the implementation of a multi-region and multi-cloud data strategy for high availability, disaster recovery, and Azure Blob Storage compliance
- Experience with big data infrastructure at scale, such as Spark, Iceberg, S3, Airflow, YARN, and Celeborn - Experience with database internals and/or with Kubernetes
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: - Data Orchestration (Airflow) - Batch Compute (Spark, Celeborn)

Your next step

Complete your application on stripe.com. The employer’s form will show what is required.

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Demand for Data Leadership roles

New Data Leadership postings at the employers we follow are about the same over the last 6 weeks compared with the 6 before.

Weekly new Data Leadership postings at the same employers, from the week of August 17 to the week of November 2. The fewest in a week was 754, the most 1,166, and the latest week had 892.
August 17Last week

Each bar is one week of new postings. The darkest bars are the last 6 weeks.

Counted from the hiring pages we’ve followed for at least five weeks, so employers we add don’t look like growth. Updated weekly.

About the role

We file this job under Data Leadership, by the work the posting describes.

Data leaders run data teams or design how a company's data fits together. Managers hire, set priorities and answer for whether the data work pays off; architects choose the systems and the shape of the data.

Expect years of hands-on data work, experience leading people or projects, and the ability to explain tradeoffs to executives.

Unlike a senior engineer or analyst, most of a data leader's week goes to people, planning and decisions rather than building.

US government figures for computer and information systems managers

Median yearly pay, May 2025
$175,140
Expected change, 2025 to 2035
15.8% more jobsagainst 3.5% for all jobs

The government has no code for data leaders, so these figures are for the closest group, computer and information systems managers, which includes data processing and data operations managers.

Source: US Bureau of Labor Statistics, Occupational Employment and Wage Statistics (May 2025) and Employment Projections (2025 to 2035). Occupation code 11-3021.

Job description

View original posting ↗

Who we are

About Stripe

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.

About the team

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:

  • Data Orchestration (Airflow)
  • Batch Compute (Spark, Celeborn)
  • Data Lake (Iceberg, Hive, S3, Azure Blob Storage)

We support over 2,000 engineers and 600+ internal teams, processing workloads that organically grow more than 30% year over year. 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.

What you’ll do

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. 

Responsibilities

  • Serve as the technical leader for the Big Data Infrastructure organization, overseeing distributed systems that manage 20% of Stripe's total AWS spend
  • Execute Stripe's transition to the "Agentic Era" by building invisible infrastructure that empowers AI agents to author, validate, ship, and operate data pipelines
  • Drive the architecture and delivery of critical modernization bets, including YARN to Kubernetes migrations, native vectorization (Gluten/Velox), and Airflow and Data Catalog modernization
  • Lead the implementation of a multi-region and multi-cloud data strategy for high availability, disaster recovery, and Azure Blob Storage compliance
  • Reduce operational burden and maintenance overhead (KTLO) from over 40% to under 10% by shifting fixes into the platform instead of relying on runbooks
  • Foster a culture of operational excellence and mentor engineers at various stages in their careers, up to Staff+

Who you are

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.

Minimum requirements

  • BS or MS in Computer Science or a related field
  • This is a Senior Staff role, so ideally 12+ years of professional experience in a software development role
  • A strong engineering background in distributed infrastructure and/or platform services, including one or more of the following: storage, databases, or compute
  • Experience leading projects on a cross-team and company-wide scale, including scaling and migrating systems with little to no downtime
  • Experience developing, maintaining, and debugging distributed systems while optimizing their reliability and security
  • Experience driving a culture of operational excellence, with a deep understanding of metrics, alerts, and dashboards

Preferred qualifications

  • Experience driving AI-led architectural transformations and integrating agentic workflows into large-scale data systems
  • Experience in a development team at AWS, Azure, OCI, or Google
  • Experience with big data infrastructure at scale, such as Spark, Iceberg, S3, Airflow, YARN, and Celeborn
  • Experience with database internals and/or with Kubernetes
Source details

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