At Google, data drives all of our decision-making. As part of the Finance Business Intelligence team, you will use data to inform business and product decisions across the company. Using your technical skills, business acumen and creativity, you will build tools to automate reporting and generate insight that will allow clients to quickly and accurately see how our key business products and processes are performing. Previous experience managing finance systems projects, with emphasis on providing business intelligence and data driven insight through reporting, will have equipped you well for this role. You’ll be involved in projects from inception to delivery, ensuring that your reporting delivers high-quality and relevant data to intelligently grow our business. You will also have extensive knowledge of key financial systems, such as Oracle and Hyperion, and experience working with a range of other business intelligence tools and platforms.
The Cloud Finance BI team supports the broader Cloud Finance organization and Cloud senior leadership. The team owns the financial analytics and automation roadmap and works with Finance and Engineering partners to build stable reporting, forecasting, simulation and modeling assets. Our goal is to enable decision intelligence while reducing the reporting burden on analysts.
In this role, you will control the Cloud P&L, drive modeling, forecasting and automation efforts and lead data science initiatives to advise on optimal HC resource allocation and drive accountability. Your deep business knowledge, data mastery, and sharp insight provide us a seat at the table as essential partners and strategic advisers to the Cloud leadership team.
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: $148000 - $215000 (USD) + 15% bonus target + equity + benefits
Learn more about benefits at Google.
Responsibilities
- Own the end-to-end lifecycle of data products: You will take full ownership of designing, developing, and maintain critical data assets for Cloud Finance, including data marts, pipelines, and dashboards. Your objective will be to build an insightful, accurate, and production-level financial reporting infrastructure.
- Drive the development of scalable models: Go beyond traditional reporting by proactively developing anomaly detection, forecasting, and what-if modeling solutions and agent skills, getting us ready for the agentic BI paradigm. You will combine your analytical acumen with innovative Google technologies to surface analytics and insights at scale, using ML and AI bring clarity to complex financial trends and new analytical capabilities to Finance.
- Lead process innovation and automation: Constantly seek out opportunities to improve our financial operations by devising new or automating existing financial models and processes, statistical or driver-based forecasts and simulations.
- Act as an accountable partner to Finance: Serve as a trusted and reliable partner to Finance colleagues across Alphabet. You will support their processes and empower them with new tools and uplevel their analytical capabilities.
- Own the narrative with executive leadership: You will be responsible for the final step: delivering insights to decision-makers. This includes automating insight-gathering processes and owning the communication of complex technical analyses to senior audiences such as Finance VPs, Directors, and Chiefs of Staff.
Qualifications
Minimum qualifications:
- Bachelor's degree in a quantitative discipline or equivalent practical experience.
- 7 years of experience in business intelligence, analytics, or quantitative analysis related fields.
- Experience programming with SQL, and an additional programming language (e.g. with R, Python, JavaScript).
Preferred qualifications:
- MA/MS 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).
- Clear written and oral communication, including the ability to communicate complex findings in a concise manner to a non-technical audience.