Senior Data Solutions Architect

At eBay were more than a global ecommerce leader were changing the way the world shops and sells. Our platform empowers millions of buyers and sellers in more than 190 markets around the world. Were 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. Were 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 organizations 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.

Key Responsibilities

• Enterprise Data Solutions Architecture

  • 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.

• Enterprise Data Architecture

  • Define and maintain enterprise-wide data domains subdomains and key subject areas.
    Design and evolve semantic data models (conceptual logical and domain-level) ontologies and enterprise taxonomies.

  • Drive alignment on architecture principles and enforce consistency across teams and platforms.

• Metadata Governance and Interoperability
  

  • Collaborate with the Data Governance leadership and align on standard metadata practices to ensure discoverability lineage and governance across corporate data domains.

  • Partner with governance AI/ML and metadata teams to enable computational governance and automated metadata enrichment.

  • Architect scalable and interoperable semantic layers across platforms (e.g. Lakehouse Knowledge Graphs Data Warehouses).
    

• Collaboration and Partnership
  

  • Collaborate with product data analytics and engineering teams to define domain focuseddata contracts that support analytics AI and operational needs.

  • Lead integration of business glossaries taxonomies and metadata systems into data platforms and AI pipelines.

  • Provide clear communication to connect business requirements with technical architecture.
    

• Frameworks and Best Practices
  

  • Design and implement reusable taxonomy and ontology frameworks that connect business context with technical systems.

  • Provide strategic guidance on modeling techniques and ensure adoption of standard processes.
    

Qualifications

• Technical Expertise
  

  • 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.

  • Deep understanding of various enterprise level business processes such as Source-to-Pay Record-to-Report Hire-to-Retire Financial Reporting and their supporting data elements.

  • 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.

• Architectural & Design Principles
  

  • Deep understanding of domain focused design data mesh principles and knowledge graph architecture.

  • Demonstrable experience integrating business glossaries metadata and taxonomies with enterprise platforms and AI systems.
    

• Leadership & Collaboration
  

  • Ability to translate sophisticated technical concepts into clear actionable guidance for both technical and non-technical partners.

  • Strong collaboration skills with experience working alongside data product owners engineers data scientists and governance teams.

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