Ebay MTS Software Engineer Data Platform 

Canada, Ontario, Toronto 

732872876

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.

• Own 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.