Competitive Data Eng & Analyst

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. About eBay eBay Inc. is a global commerce leader that connects millions of buyers and sellers around the world. We exist to enable economic opportunity for individuals, entrepreneurs, businesses, and organizations of all sizes. eBay Marketplaces operates in 190 markets worldwide. Are you looking for a company that inspires passion, courage, and imagination—where you can help shape the future of global commerce? Join eBay and help influence how millions of people buy, sell, connect, and share. About the Team The Global Competitive Strategy & Insights team delivers high-impact insights that help eBay navigate a dynamic commerce landscape. We connect market data, trends, and competitive intelligence into actionable insights that support strategic business decisions. As the team evolves, we are investing in scalable data infrastructure, automation, and self-serve analytics to improve how competitive insights are generated, operationalized, and delivered. About the Role The Competitive Data Engineering & Analytics Specialist is a hands-on role that combines data engineering, analytics, automation, and reporting. This role will help build and maintain data pipelines, integrate third-party and vendor data into eBay’s data ecosystem, and support reliable, automated, and self-serve analytics for competitive intelligence. The role will work closely with analytics, strategy, product, and data engineering partners to improve data quality, automate recurring workflows, build dashboards, and support AI-enabled analytics use cases. The ideal candidate has strong SQL skills, working knowledge of Python, experience with data pipelines or analytical data workflows, and a strong interest in building scalable, automated solutions. Key Responsibilities Build and Maintain Data Pipelines Build, maintain, and improve data pipelines to ingest, transform, and integrate third-party/vendor datasets into the data warehouse. Develop and support ETL/ELT workflows to improve data quality, reliability, and timeliness. Partner with Data Engineering teams to implement data models, optimize queries, and improve data processing efficiency. Create and maintain data schemas, validation checks, and monitoring mechanisms to improve data integrity. Automate recurring ingestion, transformation, and reporting workflows to reduce manual effort. Support Data Integration and Vendor Data Operations Support onboarding of external and vendor data sources, including requirements gathering, data validation, and pipeline implementation. Work with internal stakeholders and vendors to investigate data issues and improve data consistency. Help standardize disparate data sources into reusable and scalable datasets. Document data sources, business logic, transformation rules, and known limitations to improve transparency and reusability. Build Reporting and Visualization Solutions Develop dashboards and reporting layers using Tableau or similar BI tools. Create reusable datasets, data marts, and semantic layers to support self-serve analytics. Improve dashboard performance, usability, and maintainability through optimization and standardization. Translate business questions into structured analyses, dashboards, and scalable reporting solutions. Apply AI and Automation Use AI-enabled tools, LLMs, and automation frameworks to improve data processing, analysis, and reporting workflows. Build automated workflows to support competitive intelligence generation, recurring analysis, and insight delivery. Identify practical opportunities to reduce manual effort and improve speed, consistency, and scalability. Support use cases involving AI-assisted analytics, summarization, classification, and workflow automation. Partner with Stakeholders Collaborate with cross-functional partners across strategy, analytics, product, data engineering, and business teams. Communicate technical approaches, data limitations, timelines, and trade-offs clearly to both technical and non-technical audiences. Support long-term roadmap initiatives as well as fast-turn analytical and operational requests. Work effectively with global teams across time zones. Contribute to Operational Excellence Identify data quality, scalability, and process bottlenecks and help implement practical solutions. Contribute to best practices for data governance, pipeline reliability, documentation, and analytics workflows. Support continuous improvement of competitive intelligence data infrastructure and reporting processes. Provide input on feasibility, timelines, and implementation approaches. Requirements 3+ years of experience in Data Engineering, Data Analytics, Business Analytics, or hybrid data roles. Strong proficiency in SQL and working knowledge of Python. Experience building, maintaining, or supporting data pipelines, ETL/ELT workflows, or automated analytical data processes. Experience working with data warehouses and large datasets. Experience ingesting, cleaning, transforming, and integrating structured datasets, including third-party or vendor data. Hands-on experience with BI tools such as Tableau or similar visualization platforms. Good understanding of data modeling, ETL/ELT concepts, and data quality management. Experience automating recurring workflows, reports, or analytical processes. Familiarity with AI/ML or LLM-based tools in analytics workflows. Strong communication skills and ability to work with cross-functional teams. Ability to execute independently on well-defined problems while seeking guidance on complex or ambiguous topics. Strong problem-solving mindset, attention to detail, and willingness to learn new tools and technologies. Preferred Qualifications Experience in eCommerce, marketplaces, retail, pricing, or competitive intelligence domains. Experience building reusable datasets, reporting layers, or analytics frameworks. Exposure to AI agents, prompt engineering, or workflow automation frameworks. Exposure to Kubernetes or containerized deployment environments is a plus. Experience with cloud-based data platforms, orchestration tools, or modern data stack technologies. Strong documentation habits and ability to make data assets easy to understand and reuse. Additional Details eBay is an equal opportunity employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, national origin, sex, sexual orientation, gender identity, veteran status, and disability, or other legally protected status. If you have a need that requires accommodation, please contact us at . We will make every effort to respond to your request for accommodation as soon as possible. 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