Business Intelligence Analyst (Signals & Revenue)

Digital Media Solutions (DMS) is a performance-driven digital marketing company that connects consumers and brands through data, technology, and proprietary media platforms. The Business Intelligence Analyst will help build and maintain the company's Single Source of Truth for signal activity and revenue performance, working with large-scale datasets to provide insights that support product performance and strategic decision-making.

Responsibilities:

• Design and write complex SQL queries to aggregate signal data from DataBricks and AWS
• Structure large-scale event data into a centralized data warehouse
• Build and maintain data models that define core business metrics
• Ensure Finance, Technology, and Business teams are working from consistent and reliable data
• Lead the transition from legacy reporting tools to Looker
• Develop LookML models and dashboards tracking: Signal volume, API performance, Customer activity trends
• Partner with Finance to measure: Unit economics, Margin by signal type, Revenue attribution
• Partner with Technology teams to monitor signal delivery and data health using AWS logs and Datadog
• Partner with Business Units to build profitability views showing which signal channels drive the most value
• Maintain data integrity across Last Activity API and Activity Signal products
• Identify and resolve data discrepancies and latency issues before they impact reporting or billing accuracy

Requirements:

• 3+ years of experience in business intelligence, data analytics, or data engineering environments
• Experience working with large-scale datasets
• Advanced SQL with the ability to query large, complex datasets
• Experience working in cloud data environments such as AWS and DataBricks
• Experience building dashboards and data models in Looker (LookML) or leading a migration to Looker
• Experience working with event-based data, API logs, or streaming data
• Experience with SparkSQL or DataBricks Lakehouse architecture
• Ability to translate large datasets into clear business insights and performance metrics
• Strong understanding of financial metrics such as LTV, CAC, and gross margin
• Ability to work cross-functionally with Finance, Engineering, and business stakeholders
• Familiarity with Datadog for monitoring data pipelines and system performance
• Experience analyzing API products, signal data, or event-driven systems