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Sr. Data Engineer
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eBay

Sr. Data Engineer

Toronto, ON, Canada

Full-time

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Job details

Job type: Full-time
Experience: 3+ years of professional experience in software design and development, specifically in data pipelines and backend services.
Posting language: English
Posted: Aug 21, 2026

Original job description

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

Category

Requirements

Education

B.Sc. or M.Sc. in Computer Science, or equivalent professional experience.

Experience

3+ years of professional experience in software design and development, specifically in data pipelines and backend services.

Languages

Proficiency in Python, Java, and Scala, with a strong foundation in data structures and multithreading.

Data Tools

Expertise in distributed processing frameworks: Kafka, Spark, and Flink.

Platform

Hands-on experience with Databricks and AWS cloud environments.

Workflow & Quality

Experience with Airflow for orchestration and DBT for transformation.

Observability

Familiarity with data reliability tools such as Monte Carlo or Great Expectations.

Architecture

Solid understanding of distributed system design, relational databases, and NoSQL technologies.

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.

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More about this job

Responsibilities

The role involves architecting, designing, and developing high-performance, scalable real-time and batch data pipelines. You will also be responsible for managing data orchestration, ensuring data quality, and collaborating with cross-functional teams to support data-driven initiatives.

Requirements

Candidates must have a B.Sc. or M.Sc. in Computer Science and at least 3 years of professional experience in software design and data pipeline development. Proficiency in Python, Java, and Scala, along with hands-on experience in distributed frameworks like Kafka, Spark, and Flink, is required.

Skills

Python
Java
Scala
Kafka
Spark
Flink
Databricks
AWS
Airflow
DBT
Monte Carlo
Great Expectations
Data Engineering
Distributed Systems
NoSQL
Relational Databases

Visa sponsorship

Not detected in the job text

Keywords

Data Engineering
Python
Java
Scala
Kafka
Spark
Flink
Databricks
AWS
Airflow
DBT
Monte Carlo
Great Expectations
Distributed Systems
NoSQL
Relational Databases
Data Pipelines
Cloud Architecture
E-commerce
Agile
Scrum
JIRA
Data Quality
Backend Services
Data Structures
Multithreading
Object-oriented Design
MVC
Scalability
Data Ecosystem

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