Engineering Manager, Data Engineering

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.

We are experts in data, working to make it cost-effective, understandable, and trustworthy. We build pipelines processing billions of events a day and are stewards of canonical data warehouses and datasets delivering products for Stripe Users while embedding with teams to build their data products.  We are experts in using the Stripe Data Platform and to scale we lead the data culture and data education to enable product teams to own their data. We invest in [AI] Data Ops to scale incident handling and serve as an escalation path for data incidents to minimize their impact. The Data Engineering Solutions team will work closely with product teams delivering trustworthy data.

What you’ll do

We are looking for a hands-on Tech lead Manager to architect, build, and maintain the core data infrastructure powering Stripes business operations. This person will set the technical direction and lead a high-impact team working across Treasury, Finance & Billing. The ideal candidate combines deep technical expertise in modern data systems including Airflow/Spark/Kafka/Flink with the ability to partner closely with business stakeholders, shape team culture and unlock new capabilities.
You will:

• Deliver cutting-edge data pipelines that scale to users' needs, focusing on reliability and efficiency.
• Lead and manage a team of ambitious, talented engineers, providing mentorship, guidance, and support to ensure their success.
• Drive the execution of key reporting initiatives for Stripe, overseeing the entire development lifecycle from planning to delivery while maintaining high standards of quality and timely completion.
• Collaborate with product managers and key leaders across the company to create a shared roadmap and drive adoption of canonical datasets and data warehouses, use golden paths, and ensure Stripes are using trustworthy data.
• Understand user needs and pain points to prioritize engineering work and deliver high-quality solutions that meet user needs.
• Provide hands-on technical leadership in architecture/design and development of the datasets. 
• 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.

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.

We’re looking for someone who has: 

• 2+ years managing high performing data engineering teams, as well as 7+ years of shipping Data Products/Data Warehouses/Big Data Infrastructure and critical distributed system infrastructure.
• Proven success in recruiting and building great teams.
• Extreme customer focus, with a commitment to partnering with Product Managers, leaders, and other Stripe engineers to understand their use cases.
• Effective cross-functional collaboration, with the ability to think rigorously, communicate clearly, and make or coordinate difficult decisions and trade-offs.
• Thrives with high autonomy and responsibility in an ambiguous environment.
• Technical acumen to drive clarity with staff engineers on architecture and strategic technical decisions.
• Ability to foster a healthy, inclusive, challenging, and supportive work environment.

• Experience Tech leading, mentoring and managing a team that shipped products to data users and operated large-scale, high-availability data transformation pipelines. 
• Expertise in Iceberg, Kafka, Change Data Capture, Flink, Spark, Airflow, Hive Metastore, Pinot, Trino, AWS Cloud, and influencing open-source contributions is a plus.
• Genuine enjoyment of innovation and a deep interest in understanding how things work, with the ability to question and direct architectural decisions.
• Strong written and verbal communication skills for various audiences, including leadership, users, and company-wide.