The mission of The New York Times is to seek the truth and help people understand the world. That means independent journalism is at the heart of all we do as a company. It’s why we have a world-renowned newsroom that sends journalists to report on the ground from nearly 160 countries. It’s why we focus deeply on how our readers will experience our journalism, from print to audio to a world-class digital and app destination. And it’s why our business strategy centers on making journalism so good that it’s worth paying for.
About the Role:
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.
Responsibilities:
Capacity & Forecasting
- 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.
Architectural Optimization
- 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.
Tooling, Signals & Reporting
- 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.
Partnership, Influence & Enablement
- 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.
- This role reports to the Director of Engineering, Developer Platforms.
Basic Qualifications:
- 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.
Preferred Qualifications:
-
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).
REQ-019976
Additional Compensation and Benefits
For roles in the U.S., dependent on your role, you may be eligible for variable pay, such as an annual bonus and restricted stock. Benefits may include medical, dental and vision benefits, Flexible Spending Accounts (F.S.A.s), a company-matching 401(k) plan, paid vacation, paid sick days, paid parental leave, tuition reimbursement and professional development programs.
For roles outside of the U.S., information on benefits will be provided during the interview process.
Candidate Use of GenAI Tools
We’re excited to learn more about you and your experience. To keep our hiring process as fair and authentic as possible, we ask that you submit your own work and not use GenAI tools to generate substantive content during the application and interview process.
If you’re an Engineering candidate, we’ll let you know what specific GenAI tools you are permitted to use for your technical assessment.
The New York Times Company is committed to being the world’s best source of independent, reliable and quality journalism. To do so, we embrace a diverse workforce that has a broad range of backgrounds and experiences across our ranks, at all levels of the organization. We encourage people from all backgrounds to apply.
We are an Equal Opportunity Employer and do not discriminate on the basis of an individual's sex, age, race, color, creed, national origin, alienage, religion, marital status, pregnancy, sexual orientation or affectional preference, gender identity and expression, disability, genetic trait or predisposition, carrier status, citizenship, veteran or military status and other personal characteristics protected by law. All applications will receive consideration for employment without regard to legally protected characteristics. The U.S. Equal Employment Opportunity Commission (EEOC)’s Know Your Rights Poster is available here.
The New York Times Company will provide reasonable accommodations as required by applicable federal, state, and/or local laws. Individuals seeking an accommodation for the application or interview process should email reasonable.accommodations@nytimes.com. Emails sent for unrelated issues, such as following up on an application, will not receive a response.
The Company encourages those with criminal histories to apply, and will consider their applications in a manner consistent with applicable "Fair Chance" laws, including but not limited to the NYC Fair Chance Act, the Los Angeles Fair Chance Initiative for Hiring Ordinance, the San Francisco Fair Chance Ordinance, the Los Angeles County Fair Chance Ordinance for Employers, and the California Fair Chance Act.
For information about The New York Times' privacy practices for job applicants click here.
Please beware of fraudulent job postings. Scammers may post fraudulent job opportunities, and they may even make fraudulent employment offers. This is done by bad actors to collect personal information and money from victims. All legitimate job opportunities from The New York Times will be accessible through The New York Times careers site. The New York Times will not ask job applicants for financial information or for payment, and will not refer you to a third party to do so. You should never send money to anyone who suggests they can provide employment with The New York Times.
If you see a fake or fraudulent job posting, or if you suspect you have received a fraudulent offer, you can report it to The New York Times at NYTapplicants@nytimes.com. You can also file a report with the Federal Trade Commission or your state attorney general.
