Competitive Data Engineering Manager

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 guide eBay’s senior leadership in navigating a dynamic commerce landscape. We connect market data, trends, and competitive intelligence into actionable strategies that shape enterprise-level strategic decisions.

As the team evolves, we are investing in scalable data infrastructure and automation to significantly enhance how competitive insights are generated and delivered.

About the Role

The Competitive Data Engineering & Analytics Manager is a hybrid role that combines strong data engineering ownership with advanced analytics execution. This role is responsible for building and scaling end-to-end data pipelines, integrating third-party/vendor data into eBay’s data ecosystem, and enabling reliable, automated, and self-serve analytics.

In addition to owning data infrastructure, this role drives competitive analytics, builds dashboards, and accelerates the team’s AI-enabled transformation through automation and tooling.

The ideal candidate is equally comfortable designing data pipelines and delivering business insights, with a strong bias toward automation, scalability, and system thinking.

Key Responsibilities

Own Data Engineering & Pipeline Development

• Design, build, and maintain scalable data pipelines to ingest, transform, and integrate third-party/vendor datasets into the data warehouse.
• Establish robust ETL/ELT frameworks to ensure data quality, reliability, and timeliness
• Partner with Data Engineering teams to optimize data models, storage, and compute efficiency.
• Define data schemas, validation checks, and monitoring systems to ensure high data integrity.
• Reduce manual data handling by building automated ingestion and transformation workflows.

Lead Data Integration & Vendor Data Strategy

• Own end-to-end onboarding of external/vendor data sources—from scoping requirements to pipeline deployment.
• Manage vendor relationships and ensure consistent, high-quality data delivery.
• Standardize and unify disparate data sources into a coherent and scalable data model.

Build Scalable Reporting & Visualization

• Develop automated dashboards and reporting layers using Tableau (or similar BI tools).
• Enable self-serve analytics by creating reusable data models and semantic layers.
• Improve performance and usability of dashboards through optimization and standardization.

Leverage AI & Automation

• Implement AI-driven workflows (e.g., LLMs, internal tools) to automate data processing, analysis, and reporting.
• Build and deploy automated pipelines and agents for competitive intelligence generation.
• Continuously identify opportunities to reduce manual work and improve efficiency.

Partner with Stakeholders

• Collaborate across time zones with strong communication and execution discipline.
• Support both long-term strategic projects and fast-turn ad hoc requests.

Drive Operational Excellence

• Identify scalability bottlenecks and propose technical solutions.
• Establish best practices for data governance, pipeline reliability, and analytics workflows.
• Provide technical guidance on feasibility, timelines, and data methodologies.

Requirements

• 6+ years of experience in Data Engineering, Data Analytics, or hybrid roles.
• Strong proficiency in SQL, and good knowledge of Python and experience building data pipelines.
• Experience working with data warehouses.
• Experience ingesting and integrating third-party/vendor datasets.
• Hands-on experience with BI tools such as Tableau.
• Strong understanding of data modeling, ETL/ELT processes, and data quality management
• Experience automating workflows and improving data scalability.
• Familiarity with AI/ML or LLM-based tools in analytics workflows.
• Strong communication skills and experience working in global teams.

Preferred Qualifications

• Experience in eCommerce, marketplaces, or competitive intelligence domains.
• Experience building data platforms or reusable analytics frameworks.
• Exposure to AI agents, prompt engineering, or automation frameworks.

Success in the Role

• Successfully builds and scales reliable data pipelines for external data ingestion.
• Enables automated, self-serve competitive analytics across the organization.
• Reduces manual effort through strong automation and system design.

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 talent@ebay.com. We will make every effort to respond to your request for accommodation as soon as possible. View our accessibility statement to learn more about eBay's commitment to ensuring digital accessibility for people with disabilities.

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