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Salary: USD 200,000 - 250,000 / annual
StubHub is seeking a Senior Analytics Engineer to design, implement, and enhance complex financial data models and analytical pipelines. You will perform advanced statistical, predictive, and exploratory analyses on large-scale datasets using distributed cloud computing platforms including SparkSQL, BigQuery, Snowflake, and Databricks. Your responsibilities include developing and maintaining analytical data models, metrics, and datasets while ensuring accuracy, consistency, and usability for downstream analytics and reporting.
You will create sophisticated reports, dashboards, and self-service analytics tools using BI platforms such as Tableau and Looker to support data-driven decision-making across the organization. Partner with business and product stakeholders to understand complex data requirements, translating business questions into analytical solutions and communicating results and insights clearly. Apply deep expertise in financial data analysis to produce insights, forecasts, and models that support business objectives.
Collaborate closely with engineering teams on data integration and modeling approaches, bridging technical and analytical perspectives. Develop and maintain high-quality analytical code using programming languages such as Python and Java, along with configuration and markup languages including YAML, following established coding and data standards. You will work with orchestration frameworks such as Airflow and dbt to build robust data pipelines.
This role is hybrid, with telecommuting permitted up to 2 days per week. When in office, you will report to StubHub Inc. at 3 World Trade Center, 175 Greenwich Street, 59th Floor, New York, NY 10007. The role requires a Bachelor's degree in Data Science, Finance, Business Administration, or related field, plus 3 years of professional experience in analytics engineering, data engineering, or business intelligence. You must have demonstrated expertise in cloud computing platforms, SQL, Python, data modeling with orchestration tools, BI platforms, data processing, metadata management, and stakeholder collaboration.
