Senior Data Solutions Architect

About eBay

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.

As the Senior Data Solutions Architect, you will serve as the senior enterprise leader responsible for shaping and evolving the organization’s data architecture. You will provide deep expertise in complex data design, resolve complicated architectural problems, and ensure alignment between business needs and technical execution. A critical part of this role is to function as a leader capable of driving strategic enterprise level initiatives that require alignment and influence with varying levels of leadership across the company. By establishing principles, frameworks, and guidelines, you will drive scalability, interoperability, and consistency of data capabilities across the enterprise.

The right candidate will possess an end-to-end understanding of the enterprise landscape, connecting various enterprise business processes (e.g., Source-to-Pay, Record-to-Report, hire-to-retire) with their underlying technology systems. This includes deep expertise in tracing sophisticated data movements, ensuring data integrity and lineage across platforms, and clearly defining and correlating enterprise-wide data domains to support seamless analytical, operational, and AI-driven initiatives.

This role requires exceptional leadership, strong collaboration skills, and the ability to connect business meaning with technical implementation, ensuring that data is a strategic enabler of enterprise goals.

What You Will Accomplish

• Understand sophisticated business process needs and the underlying coordinated applications to design the most efficient end-to-end data pipeline solutions.
• Identify the most appropriate authoritative data sources, data transformation logic, and consumption patterns to satisfy specific analytical solutions.
• Design and enable the most optimal data architecture and pipelines to support large-scale AI/ML initiatives, ensuring data quality, lineage, and feature engineering readiness.
• Define and maintain enterprise-wide data domains, subdomains, and key subject areas.
• Collaborate with the Data Governance leadership and align on standard metadata practices to ensure discoverability, lineage, and governance across corporate data domains.
• Collaborate with product, data, analytics and engineering teams to define domain focused data contracts that support analytics, AI, and operational needs.
• Provide strategic guidance on modeling techniques and ensure adoption of standard processes.

What You Will Bring

• 10+ Years of experience in a large enterprise or consulting, implementing, supporting an industry standard enterprise solution (SAP, Workday) is a must.
• Hands-on experience at a functional level as a business analyst, product analyst or a product manager (10+ Years) supporting at least one enterprise solution such as SAP or Workday, focusing on data management, integrations and reporting is a must.
• Extensive experience (8+ years) in enterprise data modeling (conceptual, logical, and physical), ontology engineering, and metadata architecture.
• Proficiency (5+ years) in enterprise data modeling tools such as Alation, Atlan, Erwin, Lucidchart, or similar platforms.
• Proficiency in reporting & analytics tools (Tableau, Looker), SQL, data profiling methods and tools, ETL tools (Alteryx, Powerquery, Informatica, Talend), master data management principles, big-data solutions, hybrid cloud solutions capability is desired.
• Deep understanding of domain focused design, data mesh principles, and knowledge graph architecture.

Key skills/competency

• Data Architecture
• Enterprise Solutions (SAP, Workday)
• Data Modeling
• AI/ML Data Pipelines
• Data Governance
• Data Lineage
• ETL Tools
• SQL
• Big Data Solutions
• Knowledge Graph