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Deliver onboarding, ongoing training, reinforcement, coaching, and certification programs for Sales and Customer Success teams across AMER. Partner with sales leaders and cross-functional enablement teams to adapt global programs, diagnose field needs, facilitate live and virtual sessions, and drive measurable behavior change. Use field feedback, performance data, project management tools, and AI to improve enablement effectiveness. The role requires strong facilitation, sales methodology knowledge, technology industry familiarity, relationship-building, independent execution, and approximately 25% travel.

Supports enterprise sales leadership across the Americas by analyzing business performance, identifying revenue and sales-effectiveness opportunities, planning headcount and territories, managing KPIs, and executing strategic initiatives. Partners with Sales, Marketing, Customer Success, and other teams on operating rhythms, forecasting, QBRs, process improvements, and cross-functional projects. Requires strong analytical, communication, stakeholder-management, and problem-solving skills, plus experience in GTM operations, consulting, investment banking, or SaaS.

The Sales Revenue Analyst supports global sales commissions and new business revenue recognition. Responsibilities include optimizing commission strategies, analyzing incentive plans, reviewing deal structures and pricing, maintaining reporting for quotas and territories, developing sales compensation programs, and improving revenue and CRM dashboards. The role partners with Sales, Finance, Growth, Strategy, and senior leadership to deliver scalable operational and analytical solutions.

Provides supervised technical support for employees, including laptop deployment and collection, account management, troubleshooting, ticketing, inventory maintenance, documentation, conference-room communications, MFA/MDM support, access management, and basic security incident response. The intern participates in orientations, team meetings, and knowledge-sharing while developing practical IT support and SaaS workflow skills during a six-month academic internship.

Software Engineering Interns will contribute to Datadog’s production systems across backend, frontend, infrastructure, data engineering, and developer tooling. Responsibilities include building distributed systems, processing large-scale observability data, improving performance and reliability, delivering technical projects from design through deployment, and collaborating with mentors. Candidates should be pursuing a relevant technical degree, possess strong computer science fundamentals, know at least one programming language, and be available for a six-month internship beginning in early to mid-2027.

Product Management Interns will support customer discovery, product initiatives, requirements definition, product-data analysis, technical demonstrations, and product communications. They will collaborate with Engineering, Design, and Product Marketing while developing expertise in Datadog’s observability platform and cloud infrastructure products.

Software Engineering Interns contribute to Datadog’s observability and security platform by building and improving backend, frontend, infrastructure, data engineering, and developer tooling systems. Responsibilities include developing distributed and cloud-native services, addressing performance and scalability challenges, delivering technical projects from design through deployment, and collaborating with experienced engineers and mentors.

Software Engineering Interns build and scale Datadog’s observability and security platform. Responsibilities include developing backend, frontend, infrastructure, data engineering, and developer tooling systems; addressing performance, reliability, and scalability challenges; and delivering technical projects from design through deployment with mentorship. Interns work with distributed systems, Kubernetes, cloud-native services, and real-time processing of large-scale metrics, logs, and application data.

Applied AI Interns will research and benchmark AI models, develop scalable generative AI and machine learning features, and deploy, monitor, and maintain production AI systems. They will analyze large-scale observability data, investigate emerging model architectures, present research, and collaborate with engineering and product teams to deliver customer-facing capabilities.

Partner with sales teams to qualify and close opportunities by delivering technical presentations, product demonstrations, proof-of-concept support, and onboarding assistance. Learn and communicate Datadog’s value proposition, provide customer feedback to product teams, resolve technical concerns, escalate bugs, and address diverse pre-sales challenges. Requires knowledge of DevOps monitoring or architecture tools, Windows or Linux systems administration, strong presentation skills, and travel of up to 25%.