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.
Cloud Data Technologies (CDT) team at eBay is responsible for all the data infrastructure and management of end-to-end data lifecycle for all eBay data from onsite to analytics use cases. We are seeking a Software Engineer passionate about data-driven technologies and architectures.
About the RoleWe are seeking MTS 2 Software Engineers to contribute to the design and development of eBay’s Core Data Platform. In this role, you will help build scalable, reliable, and cost-efficient systems that enable users to develop pipelines, manage data, and unlock insights across the company. Your work will play a key part in strengthening the foundation of eBay's data platform infrastructure.
This role is focused on Data Platform Engineering — not data engineering. While familiarity with Spark, Flink, and other tools in the Hadoop ecosystem is valuable, your primary responsibility will be building and evolving the platform itself, not just authoring data pipelines.
If you are an engineer eager to deepen your expertise in distributed data processing and platform development, this team offers the opportunity to learn, contribute, and grow.
What you’ll do and learnOwn and deliver major components of eBay’s Data Platforms — from design through production rollout.
Design and evolve distributed systems powering ingestion, streaming, lakehouse/warehouse, catalog, and governance.
Contribute to long-term architecture through design reviews and authoring architecture design documents, ensuring scalability and resilience.
Build systems that balance latency, correctness, and cost while ensuring security and compliance.
Drive operational excellence for services you own, including observability and incident response.
Collaborate across product, infra, and analytics teams to align execution with business needs.
Learn and grow in areas like governance, orchestration, and privacy engineering.
Experience designing large-scale distributed systems (compute, storage, APIs, streaming).
Ability to independently deliver complex projects from requirements to production.
Systems thinker who anticipates bottlenecks, schema evolution, and reliability issues.
Strong communication skills to influence cross-team technical outcomes.
Growth mindset with curiosity to learn new technologies.
Impact at scale: powering global analytics and ML systems.
Challenging problems: streaming, freshness/correctness, and multi-cloud resiliency.
Collaborative culture that values inclusion and knowledge sharing.
Support & growth: flexibility, benefits, and career development resources.
Focus on reliability and sustainable on-call practices.
8+ years of distributed systems or data platform experience.
Proven ability to design and deliver critical systems with impact.
Proficiency in Java/Python, CI/CD, and containerized environments.
Hands-on expertise in tools like Kafka/Flink, Spark, Delta/Iceberg, Kubernetes, NoSQL/columnar stores.
Experience in streaming and batch data platforms.
Strong foundation in algorithms and distributed design.
BS/MS in CS or equivalent experience.
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