Senior Software Engineer Data Platform

Location: Dublin, Ireland
Job Type: Full-time

eBay is a global commerce leader that connects millions of buyers and sellers around the world. We empower people and create economic opportunities for individuals, businesses, and communities. We're driven by a vision to create a more sustainable form of commerce that benefits the environment and society as a whole. Join us as we continue to innovate and shape the future of e-commerce.

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.

We’re seeking a Member of Technical Staff 1 (Software Engineer) who can work independently and is an expert in distributed systems. You’ll design and deliver well-scoped services and features that advance eBay’s Core Data Platform—improving scalability, reliability, and developer experience. This role is Data Platform Engineering (not data engineering): you’ll build and evolve the platform itself rather than author application pipelines.

• Independently design, implement, and ship distributed services and features end-to-end (design → code → tests → deploy → operate).

• Build core platform capabilities across ingestion, streaming, lakehouse/warehouse, catalog, and governance.

• Write production-grade code with strong observability (metrics, logs, traces) and SLOs, and participate in on-call for the services you own.

• Diagnose and resolve performance, scalability, and correctness issues in distributed environments.

• Contribute design docs for your areas; participate in reviews to uphold reliability, security, and cost best practices.

• Collaborate with product, infra, and analytics teams to align technical work with business outcomes.
   

• 6+ years of software engineering experience, ideally in data infrastructure or large-scale backend systems.

• Strong coding skills in Java or Python, with working knowledge of CI/CD pipelines.

• Deep understanding of distributed systems (consensus, replication, fault tolerance) and experience running them in production.

• Proven ability to build high-performance, low-latency APIs, with experience in memory, CPU, and heap optimizations.

• Deep understanding of distributed systems internals and how to apply that knowledge to build robust, high-performance platforms.

• Examples include Kafka partitioning and consumer lag handling, Flink checkpointing/state management, exactly once semantics and Spark shuffle/memory optimization.

• Proven experience designing and building scalable data pipelines using Kafka, Flink, Spark, and modern data lake formats like Delta Lake or Iceberg.

• Familiarity with modern data lake storage formats (e.g., Delta Lake, Apache Iceberg).

• Strong debugging, system design, and performance analysis skills.

• Able to work independently, make trade-offs, and deliver high-quality, maintainable code.
   

• Contributions to open-source distributed systems or data platforms.
   

• Consistently ships independent, well-scoped features/services to production with strong reliability.

• Demonstrably improves throughput/latency/cost or availability/SLOs on owned services.

• Becomes a go-to engineer for distributed-systems debugging and design conversations within the team.

• Maintains high code quality, test coverage, and quality-in-release metrics.
   

• Impact at scale: Your platform work powers analytics and ML across a global marketplace.

• Hard problems: Streaming freshness/correctness, storage/compute efficiency, multi-region resiliency.

• Collaborative culture: Inclusive team that values autonomy, craftsmanship, and knowledge sharing.

• Growth: Strong mentorship, career development resources, and sustainable on-call practices.