Principal Engineer - Data Platforms

Senior Mts Software Engineer, Data Platforms

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 looking for strong backend infrastructure engineers who are passionate about building data systems that support our real-time, batch and AI systems.

About the Role

We are seeking a Sr. MTS Software Engineers to lead the architectural vision and technical strategy for eBay's Core Data platform organization. This is a pivotal role where you will drive scalable, intelligent, and cost-efficient systems that enable users to build pipelines and manage data seamlessly. Your work will establish the foundation for the future of eBay's data platform infrastructure.

We are seeking Data Platform Software Engineers, not Data Engineers. While familiarity with Spark, Flink, and other tools in the Hadoop environment is a definite advantage, your focus will be on building the data platform rather than just creating data pipelines. If you are an engineer eager to gain an in-depth understanding of distributed data processing, this is the right team for you!

What You'll Do and Learn

• Independently lead complex, high-impact initiatives across eBay's Data Platforms, from conception to successful production rollout. You will collaborate with Product Managers to help define the vision for the data platform at eBay.

• Architectural Leadership: Own and evolve the architecture for core data platform systems, ensuring solutions are scalable, secure, maintainable, and in alignment with enterprise standards.

• System Design: Eliminate duplication across systems and ensure clear responsibility boundaries; align systems with business needs and future scalability.

• Engineering Excellence: Champion clean architecture, promote use of modern frameworks, enforce quality gates, and ensure adherence to design patterns and coding standards.

• Lead by Example: Write reference implementations, contribute to core libraries, and conduct in-depth code reviews to influence standards and uplift team capabilities.

• Cost Optimization: Propose and drive engineering solutions that reduce operational overhead, improve resource efficiency, and automate manual processes.

• Framework Development: Identify opportunities to build reusable components, services, and frameworks that accelerate feature delivery across the organization.

• Modernization: Lead migrations of legacy systems into modern architectures and cloud-native paradigms with minimal disruption and high impact.

• Collaboration: Drive complex technical discussions, build consensus across engineering, product, and operational teams, and ensure smooth delivery of cross-functional projects.

• Documentation & Governance: Create well-structured Architecture Decision Records (ADRs) and contribute to technical documentation and standards.

• Proactively address performance, security, compliance, and future-proofing of solutions while balancing latency, correctness, scale, and cost.

• Raise the engineering bar through design/code reviews, operational excellence (SLOs, observability, incident management), and scalable practices that increase velocity across teams.

• Mentorship: Act as a technical mentor, guiding senior and junior engineers on architecture best practices and advanced problem-solving.

• Introduce AI-first frameworks and reusable components that reduce developer friction and enable faster iteration.

• Automate diagnostics, monitoring, and remediation using intelligent assistants and prediction-based alerting.

• Excellent in interpersonal communication

What You Bring

• Extensive experience owning large-scale distributed data platforms (multi-PB data, high-throughput streams, global systems).

• Deep systems approach: you anticipate bottlenecks, design for reliability (reprocessing, idempotency, schema evolution), and think holistically across compute, storage, and APIs.

• Excellent decision-making and communication skills, thriving in ambiguity while aligning diverse stakeholders on the right path forward.

• Security and compliance mindset, including data privacy, RBAC/ABAC, encryption, and auditability — with the ability to partner with compliance teams on regulatory requirements.

• Proven leadership in mentoring engineers, shaping team culture, and driving organizational change in engineering practices.

• Growth mindset: continuous learner who embraces new technologies, shares knowledge internally/externally, and adapts to evolving business priorities.

Why Join Us

• High-impact mission: You will build and modernize eBay's Data Platform, which powers analytics, experimentation, machine learning, personalization, and trust and compliance on a global scale.

• Challenging technical problems: From real-time streaming at scale, to lakehouse correctness, governance, cost and performance optimization, and multi-cloud resiliency.

• Vibrant culture: A collaborative, transparent, and inclusive environment where diverse perspectives are valued, knowledge sharing is encouraged, and every engineer has a voice.

• Flexibility & support: Hybrid/remote-friendly practices, competitive compensation, global benefits, and support for learning resources, conferences, and career development.

• Always-on responsibility with balance: While you'll help lead reliability for critical services, we invest in strong operational practices and on-call sustainability.

Qualifications

• 12+ years of experience in building and operating large-scale distributed systems, with 5+ years as a staff/architect-level technical lead across multiple domains.

• Proven success in driving technical strategy and roadmaps, authoring architecture and technical vision documents, and aligning stakeholders across engineering, product, and compliance.

• Strong foundation in data structures, algorithms, and distributed systems design.

• Proficiency in Java/Python (or equivalent) and in infra-as-code, CI/CD, and containerized environments.

• Hands-on deep internal expertise in several of the following: Kafka/Flink, Spark, Delta/Iceberg, GraphQL/REST APIs, RDBMS/NoSQL, Kubernetes, Airflow.

• Experience building both streaming and batch data platforms, improving reliability, quality, and developer velocity.

• Demonstrated ability to mentor senior engineers, influence org-wide practices, and make long-term architectural decisions that unlock measurable business outcomes.

• BS/MS in CS or equivalent practical experience.

The base pay range for this position is expected in the range below:

$152,400 - $247,800

Base pay offered may vary depending on multiple individualized factors, including location, skills, and experience. The total compensation package for this position may also include other elements, including a target bonus and restricted stock units (as applicable) in addition to a full range of medical, financial, and/or other benefits (including 401(k) eligibility and various paid time off benefits, such as PTO and parental leave). Details of participation in these benefit plans will be provided if an employee receives an offer of employment.

If hired, employees will be in an "at-will position" and the Company reserves the right to modify base salary (as well as any other discretionary payment or compensation program) at any time, including for reasons related to individual performance, Company or individual department/team performance, and market factors.

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