Demand Generation Data Analyst

Philips•Nashville, TN

3d•$66,000 - $105,000•Onsite

About The Position

We’re seeking a marketing analytics professional who partners cross‑functionally to deliver advanced, AI‑driven insights across campaigns and the funnel. You’ll build real‑time dashboards, translate data into clear recommendations for leaders, and ensure high standards of data quality, governance, and automation.

Requirements

4+ years of experience in marketing analytics, business intelligence, data analytics, information systems, computer science, or a related field with at least a bachelor's degree or 8+ years of relevant experience with a high school diploma.
Strong analytical skills, including data analysis and interpretation, statistical methods, data storytelling, visualization, SQL, business intelligence tools, and process automation.
Experience working with customer relationship management (CRM) tools and marketing automation platforms such as Salesforce, Eloqua, Marketo, or similar technologies.
Proven ability to analyze marketing campaigns, lead management processes, funnel performance, attribution models, pipeline metrics, and revenue impact.
Effective business partner with strong stakeholder management, consultative communication, data quality, and process improvement experience, capable of translating complex data into actionable business recommendations.

Responsibilities

Partner cross-functionally with Marketing Insights, Data Analytics, Regional Business Marketing, and Digital Marketing teams to deliver analytics that support business objectives and drive decision-making.
Analyze campaign, funnel, and attribution performance across lead, MQL (marketing qualified lead), SQL (structured query language), opportunity, and pipeline stages. Monitor funnel health, campaign effectiveness, and marketing influence on revenue outcomes while providing actionable recommendations.
Deliver advanced analytics and AI-driven insights using Power BI, Azure Databricks, SQL, and Excel to identify trends, forecast performance, and uncover optimization opportunities.
Develop real-time dashboards, reporting, and visualizations that provide performance intelligence, enable self-service reporting, and support executive decision-making.
Ensure data quality, governance, and process integrity by identifying root causes, resolving reporting issues, prioritizing analytics initiatives, and communicating insights to technical and non-technical stakeholders.