Website Analytics Architect

<p> </p><p>Role Overview</p><p><br>The ideal candidate will architect, design, implement, and maintain a robust analytics solution for the global Adobe AEM Platform, with a strong emphasis on AI-driven insights and automation. This role defines and operationalizes an AI-enabled analytics reporting framework to guide business decisions and optimization across Healthcare and Corporate websites (350+ sites) and multiple tools/integrations with Marketing & Sales systems.

You will partner with business, IT, and data governance stakeholders to deliver scalable, compliant, and secure analytics at scale, globally.</p><p> </p><p>Responsibilities</p><p> </p><ul><li>Analytics strategy and design</li><li>Define and continually enhance an AI-enabled analytics solution design across key digital platforms, with a focus on AI-assisted data discovery, anomaly detection, and prescriptive insights.</li><li>Translate business and user needs into robust platform architectures that integrate AEM (including AEMaaCS), Adobe Launch, Adobe Analytics, Google Analytics, and AI/ML-driven BI solutions.</li><li>AI-driven data integration and automation</li><li>Lead data integration activities related to Adobe Launch, Adobe Analytics, Google Analytics, and AI-enabled data products (e.g., automated tagging, intelligent event sampling, auto-classification).</li><li>Design and implement automated data pipelines, feature stores, and self-serve analytics templates that accelerate time-to-insight while ensuring data quality and governance.</li><li>AI insights and analytics capabilities</li><li>Develop and operationalize AI/ML models to enhance analytics outputs: anomaly detection, forecasting, customer journey optimization, sentiment/brand analytics, and multi-touch attribution.</li><li>Implement AI-assisted tagging, content performance scoring, and anomaly alerts within the analytics stack.</li><li>Reporting, visualization, and storytelling</li><li>Oversee analytics reporting processes for digital marketing websites and develop scalable, AI-enabled reporting solutions and a sustainable support framework for the global organization.</li><li>Manage analytics-related documentation and ensure adherence to data privacy, governance, and compliance guidelines; establish AI fairness, bias mitigation, and explainability practices for AI components.</li><li>Coordinate external vendor discussions related to analytics architecture, AI capabilities, and data integrations; collaborate with Adobe and other vendors to enhance tools/features and advocate for the business community.</li><li>Global and cross-functional collaboration</li><li>Work across time zones with global teams; influence and mentor on AI best practices in analytics, data ethics, and data literacy.</li><li>Partner with IT and business stakeholders to drive continuous improvement and adoption of AI-enabled analytics practices.</li></ul><p> </p><p>Who you are (Qualifications, Experience & Skills)</p><p> </p><ul><li>Minimum 5+ years designing and implementing an analytics framework on AEM for multiple websites; minimum 10+ years across web technologies.</li><li>Deep experience with AEM as a Cloud Service (AEMaaCS), Adobe Launch, and Adobe Marketing Cloud.</li><li>Strong background in analytics platforms (Adobe Analytics, Google Analytics, Google Data Studio, Synthesio) and in overseeing complex data integrations.</li><li>Proven track record delivering AI-enabled analytics deployments:</li><li>Experience with AI/ML integration into analytics workflows (model deployment, monitoring, governance).</li><li>Familiarity with AI/ML use cases for web analytics, customer journey optimization, forecasting, anomaly detection, and attribution.</li><li>Multichannel and responsive web expertise; experience in global, multi-region deployments and remote/multi-time-zone teams.</li><li>Solid SDLC experience (Agile and Waterfall) with strong collaboration across business and IT stakeholders.</li><li>Excellent communication and stakeholder management skills; demonstrated ability to present complex concepts to non-technical audiences.</li><li>Healthcare domain experience or exposure is highly desirable.</li><li>Governance and ethics</li><li>Knowledge of data privacy (e.g., GDPR/CCPA), data quality, and AI ethics considerations (bias mitigation, explainability, auditability).</li></ul><p> </p><p>Nice-to-have</p><p> </p><ul><li>Experience with AI governance frameworks and model lifecycle management.</li><li>Familiarity with data visualization tools and self-service BI that leverage AI-assisted insights.</li><li>Experience building AI-powered content personalization or A/B testing optimization pipelines.</li><li>Knowledge of enterprise data catalogs, metadata management, and data lineage for AI/ML workflows.</li></ul><p> </p>