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.

At eBay, we’re more than a global ecommerce leader — we’re changing the way the world shops and sells. Our platform connects millions of buyers and sellers around the world and creates economic opportunity for individuals, entrepreneurs, businesses, and organizations of all sizes.

As we continue our tech-led reimagination of the global marketplace, we’re looking for people who are passionate about solving complex problems, building at scale, and creating experiences that make commerce better for everyone.

About the team and the role:

We are looking for a talented and passionate Senior Data Engineer to join a team building scalable, reliable data solutions that power critical experiences across eBay. This team plays an important role in eBay’s data ecosystem, enabling trusted real-time insights, analytics, experimentation, and personalized experiences for millions of customers across our global marketplace. As part of this focused C2C strategy, eBay continues to invest in the future of circular commerce and the next generation of conscious consumers. With the recent acquisition of Depop, a leading consumer-to-consumer fashion marketplace with a highly engaged Gen Z and Millennial customer base, eBay is expanding its portfolio of complementary C2C businesses while preserving the distinct brand, community, and product experience that make Depop unique.

In this role, you will architect, design, and develop high-performance real-time and batch data pipelines that process massive volumes of data with a strong focus on scalability, reliability,



and data quality. You will partner closely with Data Science, Product, Analytics, and Engineering teams to translate complex business needs into durable technical solutions and drive projects across the full engineering lifecycle.

This is a strong chance for an experienced engineer who enjoys solving complex distributed data problems, influencing technical direction through hands-on leadership, and helping raise engineering standards in a highly scaled environment. You will work with modern data technologies such as Kafka, Flink, Spark, Databricks, Airflow, dbt, and AWS while contributing to a collaborative team culture focused on innovation, operational excellence, and continuous learning.

What you will accomplish:

- Design, build, and operate scalable real-time and batch data pipelines that enable timely, trusted, and productive data consumption across product, analytics, and machine learning use cases.
- Develop reliable workflow orchestration and data transformation frameworks using tools such as Airflow and dbt to improve data availability, maintainability, and developer efficiency.
- Improve data quality and trust by implementing validation, observability, and monitoring practices that help ensure accurate and dependable datasets for downstream teams.
- Drive end-to-end delivery of major data engineering initiatives, from architecture and design through implementation, testing, deployment, and long-term production support.
- Partner cross-functionally with Data Science, Product, Analytics, and Engineering teams to understand evolving requirements, influence technical decisions, and deliver solutions that create meaningful customer and business impact.
- Raise the engineering bar by identifying scalability and performance opportunities, contributing reusable patterns and shared libraries, and continuously improving data architecture,



tooling, and operational practices.

What you will bring:

- 8+ years of progressive Data Engineering experience
- Experience in data engineering or software engineering, with solid hands-on experience building large-scale data pipelines, distributed systems, or backend data services.
- Strong programming skills in Python, Java, and/or Scala, supported by solid computer science fundamentals including data structures, algorithms, concurrency, and system design.
- Hands-on experience with modern data engineering technologies such as Kafka, Spark, Flink, Databricks, Airflow, dbt, AWS, or comparable tools for batch, streaming, orchestration, and cloud-based data processing.
- Experience designing, deploying, and supporting production-grade data solutions with a strong focus on scalability, reliability, performance, testing, and operational excellence.
- Solid understanding of distributed systems, relational databases, data modeling, and NoSQL technologies, along with experience improving data quality and observability using modern tooling or comparable approaches.
- Strong problem-solving, communication, and cross-functional collaboration skills, with the ability to own complex technical initiatives and work effectively with Product, Data Science, Analytics, and Engineering partners.

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 [email protected].

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.

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📌 Data Engineer Manager - Depop (Toronto)
🏢 eBay
📍 Toronto