Business Intelligence Analyst II

Cox Automotive is seeking a Business Intelligence Analyst II to turn complex telecommunications and media data into actionable insights. In this role, you’ll design and maintain BI dashboards, reports, and data models that power decisions across brands like Autotrader, Kelley Blue Book, Manheim, and Dealertrack. You’ll collaborate with cross-functional teams to define KPIs, improve data quality, and automate reporting. In Cox’s people-first, inclusive culture, you’ll have opportunities to grow your skills, influence digital retail strategies, and contribute to data-driven innovation in automotive technology., * Design, develop, and maintain BI dashboards and reports to support decision-making across Cox Automotive’s brands

• Translate business questions from stakeholders into scalable data models and visualizations
• Analyze large, complex data sets to identify trends, performance drivers, and opportunities for optimization
• Ensure data quality, accuracy, and governance across reporting sources and BI solutions
• Collaborate with product, finance, operations, and marketing teams to define KPIs and reporting standards
• Automate recurring analyses and reporting processes to improve efficiency
• Document BI solutions, data dictionaries, and reporting standards for cross-team alignment
• Support ad hoc analysis requests and communicate insights through clear storytelling and presentations
• Partner with data engineering teams to enhance data pipelines and improve availability of reliable data
• Continuously evaluate and recommend new BI tools, features, and best practices

• SQLData modeling
• Business intelligence tools (Tableau/Power BI/Looker)
• ETL concepts
• Data visualization
• Relational databases (e.g., SQL Server, Oracle, Postgre
• SQL)
• Data warehousing
• KPI and metrics design
• Dashboard development
• Requirements gathering
• Statistical analysis
• Excel/Google Sheets advanced functions
• Telecommunications and media domain analytics
• Storytelling with data
• Report automation
• Version control (e.g., Git)
• Cloud data platforms (e.g., Snowflake, Big
• Query, Redshift)
• Data governance and quality assurance
• Agile/Scrum collaboration