Analytics Engineer II - Paid Search / Acquisition
About The Position
StubHub is hiring an Analytics Engineer II for its Acquisition Data & Analytics Engineering team. The team works across data engineering, analytics, and business strategy to support revenue-generating and marketing investment decisions. The role addresses data challenges across paid search and other acquisition channels, building scalable data solutions and tools that help the business make informed decisions. Work includes initiatives involving automated bidding, campaign strategy, experimentation, and attribution modeling. The position calls for strong engineering fundamentals, a business-oriented mindset, and curiosity about improving existing approaches. The engineer will own meaningful projects, influence technical direction, and help develop how StubHub measures and optimizes acquisition performance. With an established data foundation, the role emphasizes innovation, experimentation, and new capabilities that deliver measurable business impact. The role is hybrid, with three days in the office and two days remote, and is based in New York, NY or Century City, CA.
Requirements
- Approximately 5 or more years of relevant experience in analytics engineering, data engineering, or a closely related technical analytics role.
- Strong SQL proficiency and hands-on experience developing, transforming, and maintaining analytical data models.
- Solid understanding of data modeling concepts, data engineering principles, and best practices for scalable, reliable data solutions.
- Experience independently owning technical projects, navigating ambiguity, and delivering solutions to complex business problems.
- Ability to connect technical work to business objectives and communicate effectively with technical and nontechnical stakeholders.
- Strong problem-solving skills, intellectual curiosity, and a proactive, resourceful approach to identifying and addressing challenges.
- Experience collaborating across teams, contributing ideas, and taking ownership without extensive direction.
Nice To Haves
- Experience with marketing attribution modeling, including multi-touch attribution.
- Exposure to paid search, performance marketing, digital acquisition, or marketing analytics.
- Experience with marketing experimentation, campaign optimization, or automated bidding systems.
- Experience building automated data workflows or developing monitoring and alerting solutions.
- Experience working with complex, high-volume data in a marketplace, e-commerce, or similarly data-driven environment.
Responsibilities
- Design, develop, and enhance scalable data models and analytics solutions for paid search and broader acquisition channels.
- Build data-driven solutions to improve marketing performance, campaign optimization, automated bidding, and acquisition strategy.
- Develop and improve measurement frameworks for marketing effectiveness, experimentation, and attribution across acquisition channels.
- Build and optimize automated workflows to improve the scalability and efficiency of acquisition analytics and operations.
- Develop monitoring and alerting solutions to identify performance changes, emerging trends, and opportunities across acquisition channels.
- Apply sound data engineering and modeling principles to build reliable, maintainable, and scalable analytical solutions.
- Partner with engineering, analytics, and acquisition stakeholders to translate complex business problems into actionable technical solutions.
- Independently drive projects from problem identification through implementation and proactively identify opportunities to improve systems and processes.
- Contribute to technical discussions, share ideas, and help shape the team's long-term analytics and engineering strategy.
Benefits
- Accelerated growth environment with autonomy to lead experiments and tests at scale.
- Competitive base compensation, equity, and upside tied to impact.
- Unlimited Flex Time Off.
- 401(k).
- Health insurance.
- Vision insurance.
- Dental insurance.
- Paid parental leave.
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What This Job Offers
Job Type
Full-time
Career Level
Mid Level
Education Level
No Education Listed
