Engineering Manager, Data Transformation
StripeN/APosted 14 April 2026
Job Description
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
The Data Transformation team is responsible for building and operating batch and real time transformation pipelines and platforms for 400+ product teams at Stripe. We're aiming to make data development and management workflow at Stripe a breeze with emphasis on producing high quality datasets used for critical analytics, dashboards and workflows at Stripe. The Products owned by this team are widely adopted with 800+ weekly active users improving developer productivity for data users by many folds. The team is in an interesting phase of innovation tied to topmost priority for Stripe building and executing the strategic roadmap for streaming transformation, incremental processing and ergonomic data modeling.
We empower our users ranging from Data Scientists to Engineers building pipelines to create exceptional Stripe product experiences while providing a robust transformation platform for critical dashboarding, analytics and workflows at Stripe including user-facing reporting products Sigma and Radar .
We adopt a combination of open source technologies and in-house built software to ensure high scalability, reliability, and usability of our transformation offerings. Key example technologies used include: Spark, Airflow, Iceberg, Hive, S3, SQL, Python, Scala, GRPC, Kafka and FlinkSQL.
What you’ll do
As an Engineering Manager of the Data Transformation team, you will lead a team of engineers, collaborate with infrastructure and product engineering orgs, and advance the Data Transformation roadmap and adoption at Stripe. You will be driving critical workstreams for Stripe’s topmost priorities around delivering high quality, materialized datasets Stripe products and AI agents.
You will:
Deliver infrastructure and services that scale to our users needs with an eye on reliability and efficiency
Lead and manage a team of talented engineers on the team, providing mentorship, guidance, and support to ensure their success
Work with high-visibility teams and their stakeholders to support the Infrastructure’s key engineering initiatives
Understand user needs and pain points to prioritize engineering work and deliver high quality solutions that meet user needs
Drive the execution of projects, overseeing the entire development lifecycle from planning to delivery, while maintaining high standards of quality and timely completion
Provide hands-on technical leadership (architecture/design, vision/direction/requirements setting, and incident response processes) for your reports
Work with leaders across the company to create and drive toward the longer term vision of Stripe’s Data Transformation roadmap
Foster a collaborative and inclusive work environment, promoting innovation, knowledge sharing, and continuous improvement within the team
Partners with our recruiting team to attract and hire top talent, and define the overall hiring strategies for your team
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
We’re looking for someone who has:
1 - 3 years of experience managing teams that shipped and operated data pipelines and critical distributed system infrastructure
Successfully recruited and built great teams.
Extreme customer focus, committed to investing in partnerships with other Stripe engineers ... (truncated, view full listing at source)
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