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Senior Analytics Engineer

StubHub LogoStubHub
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Salary

$180,000 - $220,000

Location

New York, NY or Los Angeles, CA

Posted

Today

We’re rebuilding our data foundation from the ground up - and we’re looking for a Senior Analytics Engineer who thrives at the intersection of data infrastructure, business context, and cross-functional collaboration. If you're excited by the idea of owning foundational systems that will power pricing, personalization, experimentation, and more—this role is for you.

About the Team

As a Senior Analytics Engineer at StubHub, you’ll be a force multiplier for the entire company. You’ll build scalable data products and frameworks that empower analysts, data scientists, and business leaders to make better, faster decisions. You'll bring order to chaos, anticipate data needs before they arise, and partner with stakeholders across engineering, product, and business teams to help us unlock the full value of our data.

What You'll Do

  • Own the development of cross-functional data models, core business metrics, and self-service dashboards/tools.
  • Build, document, and maintain robust data pipelines using tools like dbt, Airflow, Snowflake, BigQuery, or Databricks.
  • Anticipate and solve common data access patterns across product, marketing, finance, and operations teams.
  • Partner closely with data scientists, analysts, and software engineers—often serving as the bridge between product needs and data infrastructure.
  • Define and scale analytical frameworks that support experimentation, decision-making, and business health monitoring.
  • Act as a domain expert in one or more business areas (e.g., pricing, supply, demand, user growth), becoming a go-to thought partner for leadership.
  • Support real-time and batch data workflows, data governance practices, and metadata/catalog tooling.

What You've Done

  • 5 - 10 years of experience in analytics engineering, data engineering, or business intelligence in a fast-paced, high-growth environment.
  • Expert SQL skills and strong proficiency in Python (or another programming language like Java).
  • Hands-on experience building data pipelines and models with tools like dbt, Airflow, and Snowflake (or equivalent).
  • Experience with BI tools such as Looker, Tableau, or Mode, and a strong understanding of enabling self-serve analytics.
  • Familiarity with both batch and streaming data processing patterns.
  • An ability to translate messy, real-world business problems into elegant, scalable data systems.
  • A collaborative mindset with a passion for partnering with non-technical stakeholders to unlock insights and drive impact.
  • Familiarity with data governance, observability, and metadata management tools is a plus.

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