Top Data & Analytics Jobs

Lead cross-functional analyses and build scalable reporting for go-to-market teams. Develop and automate data pipelines, create interactive dashboards, improve data quality, and translate complex findings into actionable recommendations for stakeholders and executives.

Design, implement, and support database and data-movement solutions across platforms. Develop advanced SQL, PL/SQL, and shell scripts; optimize queries; maintain schemas/views; troubleshoot production data issues; work with ETL/BI tools and engage stakeholders to meet analytics requirements within SDLC.

Develop and maintain datasets for visualization and machine learning; automate data pipelines; partner with teams to build data products.

Design, develop, and maintain ETL pipelines, databases, and data visualizations to support 300mm semiconductor manufacturing. Analyze operational performance, automate data extraction, troubleshoot systems, collaborate with stakeholders, and integrate emerging technologies to improve manufacturing efficiency.

Design, build, and maintain scalable ELT pipelines and data models for insurance (Guidewire) domains and Generative AI. Ensure data quality, performance, governance, and security; support analytics, AI model training (embeddings, vector DBs), dashboards, testing, and mentoring.

Lead cross-platform research by integrating ratings, syndicated and proprietary data (including Nielsen) to produce actionable analyses and tournament presentations. Advise on sports media trends and rights, respond to ad-hoc requests, identify research best practices, and manage/develop a junior analytics team to inform strategic decisions across Tennis Channel platforms and clients.

Design, build, and maintain the company data warehouse and ETL processes. Partner with business teams to define data solutions and visualizations, support reporting (SSRS, Crystal Reports) and BI (Power BI/Tableau), troubleshoot issues, and provide occasional after-hours support.

Build and maintain scalable data processing pipelines and the data warehouse, write tested performant code, develop product features, establish data engineering standards, and collaborate across product and engineering to improve data access and quality.

Lead growth analytics for Spark: analyze large datasets, design event tracking, build dashboards, run and validate experiments, model forecasting and LTV, ensure measurement/attribution integrity, and surface growth opportunities to product and marketing teams.

Lead development of scalable marketing data models, pipelines, and BI solutions. Partner with Marketing to define metrics, build dashboards, enable self-service analytics, and drive data governance and best practices.