Marketing Data Science & AI Operations Manager

Marketing Data Science & AI Operations Manager

Join our growing Marketing Technology & Operations Team as the Marketing Data Science & AI Operations Manager!

In this role, you will become the lead engineer of SUSE's predictive growth engine. Reporting to the Senior Director of Marketing Operations, you are responsible for the technical execution and maintenance of a unified source of truth for engagement, pipeline, and conversion.

This role is designed for a hands-on technical leader who bridges the gap between raw data and actionable intelligence. Your mission is to manage the Google Data Suite, Salesforce, and AI frameworks to build and scale autonomous analytics workflows. You ensure our predictive models are accurate, our data pipelines are resilient, and our AI deployments adhere to global data sovereignty standards.

Operational & Technical Responsibilities

• Data Architecture Implementation: Lead the end-to-end data flow between our marketing stack and Google Cloud Platform (GCP). Serve as the primary technical owner of the BigQuery environment, ensuring data across SLES, Rancher, and AI portfolios is normalized, clean, and ready for analysis.
• AI & Agentic Workflow Deployment: Scale the organization's move toward "Agentic Analytics." You will build, test, and deploy autonomous workflows using Looker Studio and AI frameworks (like Amazon Bedrock) to automate lead scoring and propensity-to-buy modeling.
• Technical Sovereignty & Compliance: Act as the technical lead for EU Data Sovereignty (GAIA-X) and GDPR 2.0 implementation. You ensure that our data residency configurations and AI training sets meet the highest global compliance standards through rigorous technical auditing.
• Predictive Modeling & Forecasting: Manage the deployment of ML models that move the Marketing Leadership Team from reactive reporting to proactive forecasting. You provide the technical backbone for 18-month forecasts on churn, LTV, and pipeline velocity.
• Unified Signal Integration: Execute the integration of disparate signals from web, product, and community into a functional Knowledge Graph. You ensure the CMO and CRO have access to a reliable, real-time view of marketing's impact on revenue.
• SME Partnership & Mentorship: Serve as the technical Subject Matter Expert (SME) for the marketing organization. You translate complex data science outputs into usable business insights and mentor regional hubs on how to leverage AI signals effectively.
• Stack Performance Optimization: Partner with the Senior Director to monitor the data-tech budget. You are responsible for the technical optimization of GCP and AWS consumption to ensure maximum ROI and system performance.

What You'll Bring

• Technical Profile: 8–12 Years in Data Science or Business Intelligence: Proven track record of managing data pipelines and analytics in a high-growth enterprise tech environment.
• Mastery of Google Data Suite: Expert-level proficiency in BigQuery, Looker Studio, and Google Cloud Vertex AI. Hands-on experience with Google Analytics and Search Console is essential.
• Good knowledge of EU Data Sovereignty (GAIA-X) and GDPR regulations
• Salesforce Proficiency: Advanced experience extracting, transforming, and reporting on complex Salesforce data structures to drive sales/marketing alignment.
• AI/ML Implementation: Practical experience building and maintaining agentic workflows, LLM-based discovery models, and predictive algorithms in a production environment.
• Global Execution: Experience managing data schemas and localization requirements across EMEA, APJ, and the Americas.

Core Competencies:

• Operational Execution: Drives systemic efficiency in the data pipeline; ensures 100% data integrity and availability for the global marketing engine.
• Analytical Reasoning: Expert at identifying and fixing "friction" points in the sales funnel using data-driven feedback loops.
• Business Acumen: Understands how technical data architecture supports quarterly and annual revenue targets.
• Developing People: Actively shares technical expertise and mentors junior team members or cross-functional peers on data best practices.

Metrics of Success:

• Pipeline Reliability: Uptime and accuracy of the global "Revenue Truth" database and BigQuery environment.
• Model Precision: The accuracy of ML-driven lead scoring and propensity models against actual conversion data.
• Operational Automation: Percentage of manual reporting tasks successfully migrated to autonomous AI workflows.
• Compliance Adherence: Successful passing of all data residency and AI governance technical audits.