At eBay, we're more than a global ecommerce leader — we’re changing the way the world shops and sells. Our platform empowers millions of buyers and sellers in more than 190 markets around the world. We’re committed to pushing boundaries and leaving our mark as we reinvent the future of ecommerce for enthusiasts.

Our customers are our compass, authenticity thrives, bold ideas are welcome, and everyone can bring their unique selves to work — every day. We're in this together, sustaining the future of our customers, our company, and our planet.

Join a team of passionate thinkers, innovators, and dreamers — and help us connect people and build communities to create economic opportunity for all.

Company Overview

eBay Inc. is a global commerce leader that connects millions of buyers and sellers around the world. We exist to enable economic opportunity for individuals, entrepreneurs, businesses, and organizations of all sizes. Our strategic vision is to become the best global marketplace through a tech-led reimagination, focusing on a culture that encourages passion, courage, and imagination. Join a purpose-driven community dedicated to creating an ambitious and inclusive workplace where you can shape the future of global commerce.

Role Overview

We are seeking a talented and passionate Data Engineer to join our team to architect, design, and develop innovative, high-performance, and scalable data pipelines. In this role, you will be at the core of eBay’s data ecosystem, building the infrastructure that enables real-time insights and powers personalized experiences for millions of users. You will have the opportunity to work with cutting-edge technologies like Flink, Spark, and Databricks to handle massive volumes of data where performance, reliability, and accuracy are of utmost importance.

Primary Job Responsibilities

• Pipeline Development: Design and develop robust, scalable real-time and batch data pipelines using Kafka, Spark, and Flink.

• Data Orchestration: Build and manage complex workflow orchestrations using Airflow to ensure timely and reliable data processing.

• Data Quality: Implement and maintain automated data quality frameworks using Monte Carlo or Great Expectations to ensure high-fidelity data across the platform.

• Cloud Architecture: Leverage Databricks and AWS to build cloud-native data solutions that improve development efficiency and system performance.

• Project Ownership: Own major data engineering projects from the design phase through coding, testing, deployment, and long-term support.

• Collaboration: Work effectively across multi-functional teams, including Data Science, Product, and other engineering leads, to provide data-driven guidance on roadmap items.

• Risk Mitigation: Identify technical risks, foresee scalability challenges, and proactively propose solutions or architectural improvements.

• Technical Excellence: Advocate for continuous improvement of the technology stack and maintain detailed documentation for all systems and pipelines.

Job Requirements

Preferred Qualifications

• Experience with Agile/Scrum methodologies and tools like JIRA.

• Experience in the e-commerce or payments domain is a plus.

• Proven track record of architecting common libraries and patterns used in large-scale applications.

• Advanced knowledge of model-view-controller (MVC) and object-oriented design paradigms.

Additional Details

This job posting relates to an existing vacancy within eBay.

eBay is an equal opportunity employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, national origin, sex, sexual orientation, gender identity, and disability, or other legally protected status. If you have a need that requires accommodation, please contact us at talent@ebay.com. We will make every effort to respond to your request for accommodation as soon as possible. View our accessibility statement to learn more about eBay's commitment to ensuring digital accessibility.

We use cookies to enhance your experience and may use AI tools for administrative tasks in the hiring process. To learn how we handle your personal data and use AI responsibly, please visit our Talent Privacy Notice, Privacy Center, and AI Hiring Guidelines.