Infrastructure Capacity Planning & Forecasting Engineer

Duties and Responsibilities

• Own end-to-end infrastructure demand forecasting across compute, storage, networking, and accelerator resources.
• Develop and maintain 12–15 month forecasts using time-series techniques (e.g., ARIMA, Prophet).
• Gather and validate inputs from product and engineering teams, incorporating business growth and roadmap signals.
• Track and improve forecast accuracy (actual vs. forecast %) and forecast stability over time.
• Build and maintain cost attribution models that allocate infrastructure spend (compute, accelerators, storage, networking, data transfer) across teams, products, and workloads.
• Develop cost-of-revenue pipelines and reporting models to provide clear visibility into spend drivers.
• Define and monitor unit cost metrics such as cost per request, cost per GB stored, and cost per pipeline execution.
• Analyze infrastructure usage to identify inefficiencies, underutilization, and cost optimization opportunities.
• Drive initiatives including:
• Rightsizing resources
• Reserved/committed usage strategies
• Spot/preemptible workload optimization
• Track utilization, efficiency targets, and cost avoidance metrics.
• Design and build scalable data pipelines and models to process large-scale infrastructure, billing, and usage datasets.
• Enable reliable ingestion, transformation, and serving of data for forecasting and cost analytics.
• Create dashboards and reporting frameworks for:
• Forecast vs. request vs. allocation
• Allocation efficiency
• Capacity utilization trends
• Support scenario analysis (what-if modeling) to guide infrastructure scaling and investment decisions.
• Deliver clear, concise insights to technical and business stakeholders.
• Promote a cost-aware engineering culture through transparency and tooling.
• Partner with SRE, infrastructure, product, finance, and procurement teams to align capacity and cost strategies.
• Establish feedback loops to inform:
• Product roadmap decisions
• Infrastructure scaling strategies
• Process and service improvements

Requirements and Qualifications

• 6+ years of experience in data engineering, analytics, or FinOps, with exposure to cloud infrastructure or capacity planning.
• Strong proficiency in Python and or Golang and SQL for data processing, modeling, and analysis.
• Experience building forecasting models and working with time-series data.
• Solid understanding of cloud infrastructure and billing systems (compute, storage, networking, accelerators).
• Experience with cost allocation methodologies and optimization techniques (e.g., reserved instances, committed use discounts, rightsizing).
• Strong analytical skills with the ability to translate complex datasets into actionable insights.
• Able to operate effectively in ambiguous, fast-paced environments with a bias for action.
• Experience with Agentic AI Development
• Experience as a Technical Project or Program Manager

Preferred Qualifications

• Experience with large-scale data processing frameworks (e.g., Spark) or cloud data platforms.
• Familiarity with SRE practices and infrastructure monitoring systems.
• Experience building data visualization and reporting solutions (e.g., Tableau, Looker).
• Exposure to FinOps frameworks and governance models.
• Strong written and verbal communication skills with experience presenting to cross-functional stakeholders.