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.

We are looking for MTS 2 Software Engineers to join the Golden Data Sets (GDS) Platform team within eBay's Core Data Platform organization.

The problem we're solving is significant: eBay currently manages over ten thousands of loosely defined datasets with fragmented pipeline implementations, resulting in widespread data duplication, redundant compute, and runaway operational costs. The GDS Platform addresses this by building a fully declarative data platform — one that accepts dataset specifications, maintains a comprehensive view of the total data flow graph, and automatically produces optimized pipelines to systematically eliminate these inefficiencies at scale.

As an engineer on this team, you will contribute to the systems that power this platform — from computation graph management to pipeline optimization and dataset lifecycle. Your work will directly reduce operational waste across eBay's data infrastructure.

Note: This is a Data Platform Engineering role. Familiarity with Spark, Flink, and the Hadoop ecosystem is useful context, but your primary responsibility is building the platform itself — not authoring pipelines.

What You’ll Do and Learn

• Build and own core components of eBay’s declarative data platform, enabling automated generation and optimization of data pipelines at scale

• Design and evolve systems that manage the global data flow graph, including dataset definitions, dependencies, and execution planning

• Develop platform capabilities for computation graph management, pipeline optimization, and dataset lifecycle orchestration

• Engineer solutions that systematically reduce data duplication, redundant compute, and operational inefficiencies across thousands of datasets

• Contribute to long-term platform architecture through design reviews and architecture documents, ensuring scalability, correctness, and resilience

• Build platform systems that balance performance, cost efficiency, and data correctness, while enforcing governance and compliance requirements

• Drive operational excellence for platform services, including observability, reliability, and incident response

• Collaborate with product, infrastructure, and data teams to standardize dataset definitions and improve platform adoption

• Develop automation and intelligent tooling to improve platform efficiency, including opportunities to leverage AI/agent-driven optimizations

• Learn and deepen expertise in areas such as declarative systems, distributed computation graphs, data governance, and large-scale platform engineering

What You Bring

• Strong experience designing and building large-scale distributed systems or platforms (compute, storage, APIs, or orchestration systems)

• Proven ability to own and deliver complex platform components end-to-end, from design to production

• Systems thinking mindset with the ability to reason about data flow, dependencies, scaling bottlenecks, and reliability trade-offs

• Experience building platform abstractions or frameworks, not just consuming them

• Strong communication skills with the ability to drive alignment across cross-functional engineering teams

• Curiosity and growth mindset to explore declarative paradigms, optimization systems, and emerging technologies

What We Bring

• Opportunity to solve foundational data platform challenges at massive scale, impacting thousands of datasets and pipelines

• High-impact work focused on eliminating inefficiencies and reducing operational cost across the data ecosystem

• Deep technical challenges in declarative systems, graph-based execution, and large-scale optimization

• Collaborative and inclusive culture with strong emphasis on engineering excellence and knowledge sharing

• Supportive environment with focus on sustainable operations, on-call balance, and long-term growth

Qualifications

• 8+ years of experience in distributed systems, platform engineering, or data infrastructure

• Strong proficiency in Java or Python, with experience building production-grade systems

• Experience with CI/CD, testing, and containerized environments

• Solid understanding of distributed system design, algorithms, and scalability patterns

• Familiarity with technologies such as Spark, Flink, or similar systems

• Experience working with large-scale data ecosystems or data platforms is a plus

• BS/MS in Computer Science or equivalent practical experience

Additional Details

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, veteran status, 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 for people with disabilities.

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