Engineering Manager, Data Transformation

at Stripe

📍 New York City, United States
📍 Seattle, United States

USD 203,400-305,200 per year

MIDDLE

✅ On-site

Tech Stack
Tag name is followed by "@" symbol and proficiency level value. About proficiency levels:

1-2 — basic awareness. Minimal hands-on experience, and a rudimentary understanding of the technology's purpose;

3-6 — daily use. Comfortable and regular usage, capable of handling common tasks and challenges related to the technology;

7-9 — you are an expert, you can teach others, you know all the pitfalls and tricks;

10 — exceptional knowledge, comprehensive understanding, and adeptness in all aspects of the technology, including advanced problem-solving. Think twice before claiming or demanding such level.

API @ 3 Airflow @ 3 Communication @ 6 Data Modeling Data Pipelines @ 5 Flink @ 3 Hive Kafka @ 3 Leadership @ 6 Python @ 3 SQL @ 3 Scala Spark @ 3 Technical Leadership gRPC

Details

Stripe's Data Transformation team builds and operates batch and real-time transformation pipelines and platforms for more than 400 product teams. The team focuses on high-quality datasets, streaming transformation, incremental processing, ergonomic data modeling, and data products supporting analytics, dashboards, workflows, Sigma, and Radar.

The team uses open-source and internally built technologies, including Spark, Airflow, Iceberg, Hive, S3, SQL, Python, Scala, gRPC, Kafka, and Flink SQL.

Responsibilities

Deliver reliable and efficient infrastructure and services that scale to user needs.
Lead, manage, mentor, and support a team of engineers.
Collaborate with infrastructure and product engineering organizations on high-visibility initiatives.
Understand user needs and pain points to prioritize engineering work and deliver high-quality solutions.
Drive projects through the full development lifecycle, from planning to delivery.
Provide hands-on technical leadership covering architecture, design, vision, direction, requirements, and incident response processes.
Work with company leaders to define and execute the long-term Data Transformation roadmap.
Foster a collaborative, inclusive, innovative, and continuously improving team environment.
Partner with recruiting to attract and hire talent and define team hiring strategies.

Requirements

Minimum Requirements

At least 3 years of experience managing teams that shipped and operated data pipelines and critical distributed-system infrastructure.
Experience recruiting and building strong teams.
Strong customer focus and a commitment to partnering with other engineers to understand their use cases.
Ability to work effectively cross-functionally, communicate clearly, and make or coordinate difficult decisions and trade-offs.
Ability to operate autonomously and take responsibility in ambiguous environments.
Technical acumen to drive clarity with staff engineers on architecture and strategic technical decisions.
Commitment to creating a healthy, inclusive, challenging, and supportive work environment.

Preferred Qualifications

Experience managing teams that shipped products to data users and operated large-scale, highly available data transformation pipelines.
Expertise in Kafka, Flink, Spark, Airflow, Python, SQL, and API design.
Enjoyment of learning and understanding technical details, with the ability to question and direct architectural decisions.
Strong written and verbal communication skills for leadership, users, and company-wide audiences.