Senior Analytics Engineer - Data (StubHub, Inc., New York, NY)

Design, implement, and enhance complex financial data models and analytical pipelines, applying advanced techniques and best practices using orchestration frameworks such as Airflow and dbt. Perform advanced statistical, predictive, and exploratory analyses on large-scale datasets, leveraging distributed cloud computing platforms including SparkSQL, BigQuery, Snowflake, and Databricks. Develop, refine, and maintain analytical data models, metrics, and datasets, ensuring accuracy, consistency, and usability for downstream analytics and reporting. Create and maintain sophisticated reports, dashboards, and self-service analytics tools using BI platforms such as Tableau and Looker to support data-driven decision-making. Partner with business and product stakeholders to understand complex data requirements, translating business questions into analytical solutions and clearly communicating results and insights. Apply deep expertise in financial data analysis, producing insights, forecasts, and models that support business objectives and extend to adjacent business domains as needed. Collaborate closely with engineering teams on data integration and modeling approaches, effectively bridging technical and analytical perspectives without assuming people-management responsibilities. 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. Telecommuting may be permitted up to 2 days a week. When not telecommuting, must report to StubHub Inc. at 3 World Trade Center – 175 Greenwich Street, 59th Floor, New York, NY 10007. Salary: $200,000 to $250,000 per year.

MINIMUM REQUIREMENTS: 

Bachelor’s degree or U.S. equivalent in Data Science, Finance, Business Administration, or a related field, plus 3 years of professional experience as a Data Scientist, Business Intelligence Analyst, or any occupation, job title, position performing analytics engineering, data engineering, and business intelligence.

Must also have experience in the following: 3 years of professional experience transforming and analyzing large scale data with modern cloud computing platforms (including SparkSQL, BigQuery, Snowflake, and Databricks); 3 years of professional experience utilizing SQL, programming languages (including Python) and markup and configuration languages (including YAML); 3 years of professional experience building data models and pipelines using orchestration software (including Airflow and dbt); 3 years of professional experience building reports and dashboards with business intelligence (BI) tools (including Tableau and Looker); 3 years of professional experience using data processing; 3 years of professional experience performing data cataloging and utilizing metadata management tools; and 3 years of professional experience working with non-technical stakeholders to understand, anticipate, and deliver data needs.

Contact: Apply Online:
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