Senior Capacity Engineer

The New York Times•New York, NY

20h

About The Position

The Cloud Cost & Capacity Engineering (CCCE) team bridges finance, engineering, data, and product to turn cloud usage and spend into strategic insight and predictable investment decisions. We enable teams across The New York Times to make smart, data-informed choices about how they use the cloud, balancing cost, capacity, and risk across AWS and GCP. As a Senior Capacity Engineer, you are the primary technical authority for how we model, plan, and optimize cloud capacity. You will own end-to-end capacity strategy for key platforms and critical user journeys (CUJs), defining how we balance headroom, efficiency, and resilience. You'll partner closely with engineering, SRE, and Finance to make sure we can handle peak moments without surprise spend or over-provisioning. This role is ideal for someone who enjoys working at the intersection of capacity engineering, architecture, and cloud economics, and who is comfortable influencing senior stakeholders without direct people management responsibility. You will sit at the center of how The New York Times manages cloud capacity and growth. Your work will directly impact our ability to support major news events, launch new products confidently, and keep cloud growth within targets—while giving teams the flexibility and clarity they need to build great experiences for our readers.

Requirements

8–10+ years in capacity engineering, cloud cost management, SRE, or platform/infrastructure engineering in a public cloud environment, partnering closely with engineering and finance on infrastructure investment and cost predictability.
Experience modeling capacity and cloud spend for large-scale, distributed systems, including forecasting, scenario planning, and cost-to-serve analysis.
Strong understanding of cloud deployment architectures (compute, storage, networking, data) and the cost and capacity drivers behind them.
Proficiency with cloud cost and usage tools (e.g., FinOut, Cloudability, AWS Cost Explorer, GCP Billing/Export) and observability platforms to derive capacity signals.
Advanced data analysis and modeling skills (e.g., Google Sheets, SQL/BigQuery) to build, validate, and communicate capacity models and forecasts—even with imperfect data.

Nice To Haves

Background in FinOps or cloud financial management, especially in high-traffic or subscription environments, and familiarity with readiness and reliability practices (e.g., load testing, capacity readiness reviews, Always Ready–style programs).

Responsibilities

Build and maintain forward-looking capacity models for major platforms, environments, and CUJs using historical trends, product roadmaps, and traffic patterns.
Translate growth (traffic, data, features, video) into infrastructure capacity plans that balance performance, resiliency, and cost.
Quantify “cost of capacity vs. risk” trade-offs and provide clear recommendations for both run-rate and new initiatives.
Partner with CCCE and Finance to improve cloud forecast accuracy and connect capacity assumptions to budgets, multi-year plans, and cloud commitments.
Partner with Cloud Engineering and platform teams to analyze scaling behavior, rightsize resources, and implement cost-efficient patterns (autoscaling, reservations/savings plans, storage policies, non-prod guardrails).
Identify systemic capacity and efficiency risks across architectures and drive solutions via guardrails, reference designs, and lifecycle automation.
Embed capacity and cost considerations into design reviews and intake for new services and cost-impacting changes.
Leverage and evolve cost and capacity tooling (e.g., FinOut, billing exports, dashboards) to produce actionable capacity signals rather than raw data.
Work with SRE and observability teams to align capacity signals (utilization, saturation, headroom thresholds) with reliability and performance goals.
Create concise views, narratives, and recommendations that help mission leads, engineering managers, and finance partners understand capacity posture and trade-offs.
Act as a technical partner to engineering teams, helping them design and operate services that are elastic, efficient, and predictable.
Mentor engineers and analysts on capacity planning best practices, modeling techniques, and how to interpret capacity signals.
Represent CCCE in cross-functional forums where cloud growth, reliability, and investment trade-offs are discussed.
Contribute to training, documentation, and office hours that make capacity planning a shared, repeatable practice across engineering.
Demonstrate support and understanding of our value of journalistic independence and a strong commitment to our mission to seek the truth and help people understand the world.