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Engineering Manager, Data Transformation

Stripe · Us · Remote available · 8122 Data Foundations

Posted Sep 30, 2026 · We last checked this listing on Oct 6, 2026

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Likely interview questions for this role

Written from this job description, not a generic list. Each one notes what the interviewer is really checking.

About your past

Tell me about a time you led a team through a migration that users didn't want to do.

What they are checking: Whether they can drive adoption with good tooling, communication and patience instead of mandates alone.

Describe how you've grown a senior engineer into a technical leader.

What they are checking: Whether they invest in people and can build leadership depth on their team.

What would you do

A finance dashboard shows wrong numbers because of a pipeline bug your platform didn't catch. What do you do?

What they are checking: Whether they handle data incidents with urgency, clear communication and lasting fixes to quality checks.

How do you keep on-call manageable for a team running platforms that hundreds of teams depend on?

What they are checking: Whether they protect reliability and team health together through sound operational practice.

Two of your engineers disagree strongly about which streaming framework to adopt. How do you resolve it?

What they are checking: Whether they can run a fair technical decision process and get the team to commit afterward.

About the work

How would you build a roadmap for moving from batch pipelines toward streaming and incremental processing for 400 product teams?

What they are checking: Whether they can plan a large platform shift with migration paths, not just pick new technology.

Walk me through the tradeoffs between full recompute and incremental processing for a critical dataset.

What they are checking: Whether they understand correctness, late-arriving data, cost and complexity in incremental pipelines.

Your platform has 800 weekly users. How do you decide which of their requests to build?

What they are checking: Whether they can prioritize a platform roadmap by user impact and strategy rather than by who asks loudest.

What does ergonomic data modeling mean to you, and how would you make it easier for data scientists to build good datasets?

What they are checking: Whether they understand the developer experience side of data platforms, which is what drives adoption.

How would you measure whether your platform is actually improving developer productivity?

What they are checking: Whether they can define meaningful platform metrics beyond raw usage numbers.

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The full job description

As published by Stripe.

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 manifold. The team is in an interesting phase of innovation tied to the 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 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'll lead a team of engineers, collaborate with infrastructure and product engineering orgs, and advance the Data Transformation roadmap and adoption at Stripe. You'll drive critical workstreams for the topmost priorities at Stripe around delivering high-quality, materialized datasets for Stripe products and AI agents. Responsibilities • Deliver infrastructure and services that scale to our users' needs with an eye on reliability and efficiency • Lead and manage a team of engineers, providing mentorship, guidance, and support to ensure their success • Work with high-visibility teams and their stakeholders to support key infrastructure engineering initiatives • Understand user needs and pain points to prioritize engineering work and deliver high-quality solutions that meet those 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 and 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 the Data Transformation roadmap • Foster a collaborative and inclusive work environment, promoting innovation, knowledge sharing, and continuous improvement within the team • Partner 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 • 5+ years of experience managing teams that shipped and operated data pipelines and critical distributed system infrastructure • Successfully recruited and built great teams • Strong customer focus, committed to investing in partnerships with other Stripe engineers to establish empathy and understand their use cases • Works effectively cross-functionally and is able to think rigorously, communicate effectively, and make or coordinate hard decisions and trade-offs • Thrives with a high degree of autonomy and responsibility in an ambiguous environment • Technical acumen to drive clarity with staff engineers about architecture and technical strategic decisions • Encourage a healthy and inclusive work environment that's both challenging and supportive Preferred qualifications • Managed teams that shipped products to data users and operated large-scale, high-availability data transformation pipelines, with expertise in Kafka, Flink, Spark, Airflow, Python, SQL, and API design • A genuine enjoyment of learning and diving into the nuts-and-bolts of how things work, with the ability to question and direct architectural decisions • Strong written and verbal communication skills for different audiences (leadership, users, company-wide)

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