• Develop and maintain capacity models for compute, storage, and network infrastructure across global environments. • Build and productionize advanced time‑series forecasts (e.g., ARIMA/ETS, Prophet, XGBoost/LightGBM) to predict demand, saturation points, and runway. • Conduct scenario modeling (“what‑if”) on deployment plans, workload changes, demand spikes, and hardware refresh strategies. • Analyze historical utilization to identify emerging risks, inefficiencies, and optimization opportunities. • Design, build, and maintain Python‑based data pipelines for ingesting, transforming, and validating large‑scale infrastructure telemetry. • Create ETL/ELT workflows to support analytics, modeling, and reporting. • Integrate data from observability platforms (e.g., Prometheus/Grafana), CMDB/asset systems, and internal services. • Develop APIs/services to expose forecast results and capacity signals to dashboards and tooling. • Build executive‑ready dashboards in Power BI (DAX, Power Query, custom visuals) and integrate real‑time forecasting outputs. • Deliver clear, compelling insights to engineering, operations, and finance leaders to support both strategic and tactical decision‑making. • Automate reporting workflows and ensure up‑to‑date visibility into runway, utilization, and risk posture. • Partner with engineering, operations, and finance teams to align capacity plans with growth, reliability, and cost objectives. • Establish standards for model governance, documentation, and data quality. • Drive continuous improvement of capacity planning systems, tooling, and analytics frameworks.