About the job

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 company decisions. Excellent at working on multiple projects at a time, you are focused on the details while finding creative ways to address big picture issues.

You are both a manager and a mentor, providing financial leadership and analytical support to partners of the core Finance team as well as giving your own team the support they need to become financial experts. You'll keep management informed on key financial metrics and work to improve financial operation practices throughout your region.

As a part of the Cloud Finance BI team, you will support the broader Cloud Finance organization and Cloud executive leadership. You will own the financial analytics and automation roadmap and work with Finance and Engineering partners to build stable reporting, forecasting, simulation and modeling assets. Your goal is to enable decision intelligence while reducing the reporting burden on analysts.

As a part of this team, you will take ownership of the Cloud P&L and drive modeling, forecasting and automation efforts alongside data science initiatives to advise on optimal dollar and headcount resource allocation and drive accountability. Your business knowledge, data mastery, and sharp insight provide us a seat at the table as essential partners and advisers to the Cloud leadership team, backed by an analytics suite that serves 500+ monthly active users across Finance and Cloud.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 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.

The US base salary range for this full-time position is $180,000-$261,000 + bonus + equity + benefits. Our salary ranges are determined by role, level, and location. Within the range, individual pay is determined by work location and additional factors, including job-related skills, experience, and relevant education or training. Your recruiter can share more about the specific salary range for your preferred location during the hiring process.

Please note that the compensation details listed in US role postings reflect the base salary only, and do not include bonus, equity, or benefits. Learn more about benefits at Google.

Responsibilities

• Lead and develop a team of Business Intelligence developers through technical coaching, standards-setting, prioritization, and task allocation, while maintaining an agile and adaptable roadmap that responds to evolving stakeholder needs.

• Collaborate with cross-functional stakeholders to translate business needs into technical requirements, provide data-driven recommendations, and drive through to deployment.

• Own the end-to-end life-cycle of data products by taking full responsibility for designing, developing, and maintaining critical data assets for Cloud Finance.

• Advance scalable model development by going beyond standard reporting to proactively developing anomaly detection, drill-down, forecasting, and what-if modeling solutions, leveraging ML and AI to surface analytics and insights at scale and bring clarity to financial trends.

• Lead process innovation and automation by constantly seeking opportunities to improve financial operations by devising new or automating existing financial models and processes.

Minimum qualifications

• Bachelor's degree in a quantitative discipline or equivalent practical experience.

• 10 years of experience in business intelligence, analytics, or quantitative analysis related fields.

• Experience in Programming and SQL.

• Experience building, developing, and leading a team.

Preferred qualifications

• Master's degree in a technical or quantitative field, or equivalent practical experience.

• Experience building data infrastructure and solutions (e.g. designing architecture, building big data pipelines, implementing scalable monitoring).

• Experience building machine learning models for forecasting or anomaly detection purposes.

• Proficiency in a programming language for data analysis and automation (e.g., Python or R).

• Excellent written and verbal communication, including the ability to communicate findings in a concise manner to a non-technical audience.