Senior Financial Analyst, Strategic TI Capacity Planning

Financial Analysts ensure that Google makes sound financial decisions. As a Financial Analyst, your work, whether it's modeling business scenarios or tracking performance metrics, is used by our leaders to make strategic company decisions. Working on multiple projects at a time, you are focused on the details while finding creative ways to take on big picture challenges.

As someone who knows the workings of the core Finance team inside and out, you'll lead individual projects to transform planning, tracking and control processes. You'll provide senior level management with insightful recommendations, planning and reporting support.

Technical Infrastructure (TI) is the backbone of Google - the global data centers, networks and integrated hardware and software that power both Google customer products and services, including Google Cloud, and our internal operations. Google builds and operates one of the largest data center fleets in the world. It is a complex technical area with very large operating and capital budgets growing year over year.

The TI Finance mission is to partner cross-functionally drive optimal decision-making, provide insights for strategic and tactical decisions, and bend the cost curve down to provide Google with a competitive advantage.

The name Google came from "googol," a mathematical term for the number 1 followed by 100 zeros. And nobody at Google loves big numbers like the Finance team when providing in depth analysis on all manner of strategic decisions across Google products. From developing forward-thinking analysis to generating management reports to scaling our automated financial processes, the Finance organization is an important partner and advisor to the business.

Individual pay is determined by factors including job-related skills, experience, and relevant education or training.

US: $141000 - $205000 (USD) + 15% bonus target + equity + benefits

Learn more about benefits at Google.

Responsibilities

• Partner closely with Capacity Planning Business teams to lead the strategic development of the long range demand plan, ensuring a coherent and synchronized demand plan across TI.
• Challenge business assumptions and identify and resolve process gaps in demand forecasts to ensure high-fidelity planning.
• Collaborate with various Finance, supply planning teams to understand their supply responses, constraints and bottlenecks. Identify and mitigate potential capacity constraints, developing contingency plans and recommending strategic investments to ensure service delivery.
• Develop financial framework, modeling and scenario planning capability to evaluate the financial outcome of infrastructure scaling, ensuring financially responsible business decisions.
• Develop metrics to measure planning efficiency and asset utilization, identify areas of improvement, challenge business assumptions, and maximize CapEx Return on Investment (ROI).

Minimum qualifications:

• Bachelor's degree in Business, Finance, Economics, Statistics, or another quantitative field, or equivalent practical experience.
• 7 years of experience in management consulting, sales operations, business strategy, investment banking, venture capital, private equity , or corporate advisory, or 4 years of experience with an advanced degree.
• 3 years of experience in project management, analysis, or capacity planning.
• Experience with financial modeling, valuation (DCF), and capital structure analysis.

Preferred qualifications:

• Bachelor’s degree in Finance, Economics, or a related quantitative field.
• 6 years of experience in business/corporate finance, banking, corporate development, or strategy consulting.
• Experience managing infrastructure capacity planning in a capital-intensive tech environment, and driving infrastructure efficiency programs.
• Experience in CapEx, OpEx long-range modeling, technical infrastructure and Cloud environments of a fast-paced technology company.
• Track record of cross-functional business partnering and collaboration.
• Understanding of the data center, ML chips, and the economics of Cloud and AI.