How much experience is required?

At least 10 years of relevant experience for this Engineering Manager, Checkout Optimization role.

What's the tech stack?

Joblaze extracted these technologies from the posting: Data Engineering, Fullstack, Machine Learning.

What seniority level is this role?

Stripe targets lead candidates for this position.

Is this full-time or contract?

Full-time for this Engineering Manager, Checkout Optimization role at Stripe.

Engineering Manager, Checkout Optimization at Stripe

Joblaze summary

The Engineering Manager for Checkout Optimization at Stripe oversees a team focused on enhancing checkout experiences through experimentation and data-driven solutions. This role requires a strong background in software development, particularly in backend systems, along with experience in managing engineering teams and driving product growth. Ideal candidates will have a proven track record in leading teams that prioritize user needs and optimize product performance. The position offers the chance to work at the intersection of engineering and product strategy within a dynamic and innovative environment.

Joblaze insights

Listed 9 days ago on Joblaze — tracked directly from Stripe's career page.
Stripe has 674 other open roles including Channel Sales Executive, SaaS Platforms, Customer Success Manager, RFA, Account Executive, Enterprise (Hunter) .
798 active Machine Learning roles on Joblaze right now.
148 active Data Engineering roles on Joblaze right now.
20 active Fullstack roles on Joblaze right now.
Typical Machine Learning salary we track runs $145,000–$230,000 (median $185,000, across 355 roles). See Machine Learning salary trends

Quick facts

How much experience is required?: At least 10 years of relevant experience for this Engineering Manager, Checkout Optimization role.
What's the tech stack?: Joblaze extracted these technologies from the posting: Data Engineering, Fullstack, Machine Learning.
What seniority level is this role?: Stripe targets lead candidates for this position.
Is this full-time or contract?: Full-time for this Engineering Manager, Checkout Optimization role at Stripe.

From the 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

The Checkout Optimization team is the growth team for Stripe’s checkout UIs. They build high-converting, personalized checkout experiences for buyers and agents, as well as the data platform that powers it.

The team identifies opportunities to improve checkout through rapid product experimentation and delivers optimization at scale through our ML-powered engine. The team also builds the reliable data foundations that enable this work, including experimentation, optimization, and data-informed product decisions across Stripe’s checkout suite.

Over the next 6 to 12 months, the team will focus on:

Building personalized checkout experiences powered by the ML-based Optimization Engine
Agentic commerce through optimizing OCS experiences for agent buyers
Checkout optimization for rapidly growing AI companies
Improving our data platform, which is critical to leveraging data internally and externally

What you’ll do

Engineering Managers at Stripe are responsible for the success of their team. You’ll be deeply involved in the engineering and design processes as well as coaching, mentoring, and leading the team. You’ll have a deep understanding of how to drive efficient engineering teams and you’ll have a strong user focus. You'll work with engineers on creating technical solutions and communicating effectively across teams and senior leadership.

Responsibilities

Lead and manage a team of talented full-stack product and data engineers, providing mentorship, guidance, and support to ensure their success
Understand buyer and agent needs and pain points to prioritize workstreams and deliver high-quality checkout experiences
Partner with Product, Design, Data Science, Data Engineering, and engineering teams across Stripe to deliver these solutions
Lead experimentation and optimization work that improves checkout conversion and buyer experiences
Build and evolve the data platform that enables reliable, self-serve analysis, experimentation, and product decisions across OCS
Drive high standards for the quality, reliability, and usability of the data products and pipelines that support OCS decision-making
Recruit top engineering talent in partnership with Stripe’s recruiting team to build a diverse and high-performing team
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, including architecture and design, vision, direction, requirements setting, and incident response processes for your team
Set the team’s direction, from north star vision to goals, OKRs, and roadmap

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 engineering management experience, directly managing and growing teams of 5+ engineers focused on building and shipping products at scale
10+ years of full-time software development experience, with a strong background in backend development
Experience working across geographies
Experience leading growth or product teams that have used experimentation to drive product usage and other metrics
Experience building extensible, leveraged software solutions that scale to different kinds of user needs, with the ability to empathize with users and advocate for excellent user experiences

Preferred qualifications

Previous experience working in payments and on payments technology
Previous experience leading a growth team
Previous experience leading a data engineering team