US Enterprise Data & Analytics Lead, Sales Operations (AI-Enabled)

As the US Enterprise Data and Analytics Lead for Sales Operations, you will serve as our technical and business intelligence expert who collaborates with data strategy, business insights delivery, and intelligent automation across the US sales organization. This role sits at the intersection of data, systems, and sales operations—requiring deep expertise in enterprise data platforms, analytics, and the ability to scale by leveraging AI and automation to solve complex business challenges. You will partner closely with the Sales Operations and Sales team to drive the strategy and optimization of critical enterprise data systems including Dun & Bradstreet (D&B), Internal customer sales data, CRM platforms, and business intelligence tools—ensuring sales teams have access to accurate, timely, and actionable insights. As the lead for business intelligence delivery, you will streamline D&B usage, design agentic workflows, and drive automation that transforms sales planning, forecasting, compensation, territory design, and performance analytics. This is a lead role where you leverage existing teams—including Business Process Requirement (BPR) managers, Analytics, Enterprise Systems, Data Science, and Engineering—to execute technical solutions. You will provide strategic direction, translate business requirements into technical specifications, and coordinate cross-functional execution. At the same time, you'll stay hands-on when innovating new solutions, prototyping agentic flows, or solving complex technical challenges. The ideal candidate is both a data expert and a business expert who deeply understands sales operations processes and can balance strategic leadership with hands-on innovation. You're passionate about leveraging AI and automation to drive business value and have the technical fluency to guide technical teams while maintaining strong business acumen. Minimum Qualifications 6+ years in Sales Operations, Data & Analytics, Business Operations, or related fields. Strong analytical skills with experience in data modeling, BI tools, and analytics platforms (e.g., Tableau, Power BI, SQL). Experience applying automation, advanced analytics, or AI/ML tools in a business context (forecasting, pipeline analysis, etc.). Technical fluency with APIs, system integrations, and middleware tools to design and troubleshoot integrations between CRM platforms and enterprise data systems. Demonstrated experience leading or coordinating technical teams including Data Science, Engineering, Analytics, or Enterprise Systems to deliver data solutions. Proven track record of data-driven decision-making with experience analyzing complex datasets and influencing business strategy. Strong business acumen with an understanding of sales operations processes (forecasting, quota planning, territory management, compensation, performance tracking). Experience with CRM platforms (e.g., Salesforce) including configuration, reporting, automation, and data management. Exceptional communication and leadership skills with the ability to translate technical concepts for non-technical audiences and provide strategic direction to technical teams. Comfortable balancing strategic leadership with hands-on innovation—able to direct teams while remaining technically engaged to prototype and validate new solutions. Preferred Qualifications Hands-on coding experience with Python or R for data analysis and automation scripting. Experience with AI/ML technologies including LLMs, generative AI applications, or designing agentic workflows and automation solutions. Expertise in Dun & Bradstreet (D&B) data platforms, including data enrichment workflows, account intelligence, and optimization strategies. Proven success leading automation initiatives that streamline processes and increase operational efficiency. Understanding of machine learning, prompt engineering, and AI applications sufficient to guide technical teams and innovate solutions. Track record of becoming a subject matter expert in complex enterprise data systems and driving strategic improvements. MBA or Master's degree in Data Science, Business Analytics, Computer Science, Engineering, or a related field.