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Manage full-lifecycle recruiting for General and Administrative roles, including sourcing, candidate screening, interview process design, candidate communication, compensation negotiation, and closing. Partner with leadership and train interview teams while maintaining accurate candidate data and reporting in Greenhouse. Deliver a strong candidate experience throughout the hiring process and manage multiple openings independently.

Lead Datadog’s Brazil Channel organization and Partner Manager team. Own channel strategy, partner recruitment and development, ecosystem expansion, partner-sourced pipeline, revenue growth, forecasting, and performance reporting. Build executive relationships with system integrators, MSPs, resellers, and technology partners while aligning with Sales, Marketing, Alliances, and Partner Solutions. Strengthen partner capabilities, certifications, services capacity, and joint go-to-market initiatives with AWS, Microsoft Azure, and Google Cloud.

Develop and execute go-to-market strategies, quota and capacity planning, KPI frameworks, incentive design, and revenue growth initiatives. Analyze sales data, build models and dashboards, identify channel efficiency trends, and support senior GTM leaders with strategic decision-making. Lead cross-functional operational projects involving Sales, Marketing, Strategy, and Product while managing multiple priorities and presenting insights to executive stakeholders.

Recruit, enable, and manage strategic channel partners (GSIs, MSPs, VARs) to drive customer adoption and revenue. Coordinate technical and marketing aspects of partner launches, run business reviews, generate partner-sourced pipeline, and collaborate with regional sales teams to close deals.

Investigate complex customer escalations involving Datadog Database Monitoring, lead technical calls, and perform root-cause analysis. Debug Datadog Agent integrations and database environments across cloud and self-hosted deployments. Partner with Engineering and Product to improve integrations, code, telemetry, documentation, and releases. Create runbooks and debugging frameworks, deliver training and office hours, mentor Global Support Engineering, and advocate for customer needs.

Provide hands-on technical guidance to enterprise customers, drive Datadog product adoption, analyze IT Operations environments, recommend improvements, lead business reviews, advocate for customer needs, and collaborate with Sales, Support, Product, Engineering, and Technical Services teams.

Develop and scale Datadog’s integrated executive thought leadership program across regions and channels. Build playbooks, operating frameworks, and repeatable processes; identify speaking and media opportunities; coordinate with communications, social, marketing, and regional teams; shape executive messaging for major business moments; and measure program effectiveness. The role requires exceptional writing, executive ghostwriting, stakeholder influence, and strategic communications experience in B2B technology or SaaS.

Design, build, and operate high-throughput data pipelines supporting billing and cost attribution. Drive Spark optimization, latency reduction, sharding, cross-datacenter reliability, and new billing capabilities. Investigate billing accuracy issues with Finance and Product teams, participate in on-call rotation, and improve engineering standards and operational excellence.

Partners with sales teams to qualify and close customer opportunities by delivering technical presentations, product demonstrations, and proofs of concept. Provides DevOps and systems administration expertise, supports onboarding and technical evaluations, resolves customer concerns, escalates bugs, communicates feature requests to product teams, and represents Datadog with customers and partners. Requires French fluency and travel of up to 25%.

Build scalable, responsive frontend features using React and TypeScript for a high-scale observability platform. Collaborate with backend engineers, product managers, and designers to refine designs, plan rollouts, and deliver user-impacting functionality. Develop reusable components, contribute to the design system, improve performance, address scalability limits, and evaluate new frontend tools and patterns. Use AI coding tools in daily workflows while maintaining code quality, simplicity, and performance.