Analytics Engineer, WNBA

WNB WNBA•New York, NY

2d•$115,000 - $130,000•Hybrid

About The Position

The Analytics Engineer, WNBA will transform data from first- and third-party systems into standardized analytical datasets that support reporting, advanced analytics, AI product development, and data enablement. Reporting to the Business Intelligence Platforms Lead, this role will serve as DSA's subject matter expert for WNBA fan, subscription, engagement, and viewership data, including WNBA ID, Evergent, Amplitude, Bitmovin, and strategic media partners.

Requirements

Advanced SQL skills with demonstrated experience developing complex analytical data models.
Experience building production-ready data pipelines and transformations using dbt or a similar analytics engineering framework.
Strong understanding of dimensional modeling, data warehousing, and analytics engineering best practices.
Experience working with cloud-based data platforms such as Snowflake, Databricks, BigQuery, or Redshift.
Experience developing semantic layers, business metrics, or reusable analytical datasets that support reporting and self-service analytics.
Familiarity with Git-based development workflows (GitHub or Azure DevOps) and collaborative software engineering practices.
Experience implementing automated data quality testing, monitoring, and documentation as part of analytics engineering workflows.
Strong communication and stakeholder management skills with the ability to translate business requirements into scalable analytical solutions.
Bachelor’s degree required with a technical or quantitative field preferred
5+ years of experience in analytics engineering, data engineering, or building analytical data models within cloud data platforms.

Nice To Haves

Experience in sports, media, entertainment, or direct-to-consumer businesses preferred

Responsibilities

Own the design and development of analytical data models that support reporting, analytics, and AI across the WNBA.
Lead the development of the WNBA's analytical data foundation by integrating fan identity, subscription, engagement, and viewership data into a unified view of the WNBA fan journey.
Identify recurring business questions and develop scalable data models and reusable datasets that reduce manual analysis and enable self-service reporting.
Develop and manage the semantic layer for WNBA analytical data, ensuring consistent business definitions and reusable datasets for reporting, self-service analytics, and AI applications.
Establish and maintain documentation, in conjunction with tools such as Alation and Confluence, to improve the discoverability, understanding, and governance of WNBA analytical data assets.
Lead data quality efforts by developing automated testing, monitoring, and validation processes to identify, prevent, and remediate data issues.
Serve as the internal subject matter expert for WNBA analytical data, partnering with stakeholders to shape analytical solutions, identify new data opportunities, and support evolving business needs.
Partner with DSA's Data Science and Analytics teams to develop analytical datasets that support advanced analytics, experimentation, machine learning, and AI initiatives.
Collaborate with internal business teams, Data Engineering, and external partners to onboard new data sources and expand the WNBA's analytical capabilities.
Continuously identify opportunities to improve analytical data models, analytics engineering practices, and the overall data foundation supporting the WNBA.