Minimum qualifications:
- Bachelor's degree in a quantitative discipline or equivalent practical experience.
- 4 years of experience in Business Intelligence, Analytics or Quantitative Analysis related fields.
- Experience in Programming and SQL.
- Master's degree in a technical or quantitative field, or equivalent practical experience.
- Experience building Business Intelligence/Online Analytical Processing (OLAP) solutions using SQL or similar query language.
- Experience building and maintaining Machine Learning models for forecasting and outlier detection purposes.
- Experience developing, running, and working with Big Data pipelines.
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About the job
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 is part of the Finance Transformation Office and 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 financial reporting, analytics, forecasting, simulation and modeling assets. The goal is to enable decision intelligence while reducing the reporting burden on analysts.
The team controls the Cloud Profit and Loss, drive modeling, forecasting, and automation efforts, as well as lead data science initiatives to advise on optimal resource allocation and drive accountability.
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.
The US base salary range for this full-time position is $118,000-$174,000 + bonus + equity + benefits. Our salary ranges are determined by role, level, and location. The range displayed on each job posting reflects the minimum and maximum target salaries for the position across all US locations. 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
- Develop, test, and maintaining data solutions, data marts, pipelines and dashboards for Cloud Finance, with the objective of building insightful, accurate, and production-level financial reporting infrastructures.
- Develop an intuitive understanding of Cloud systems and utilize the innovative Google technologies to deliver scalable forecasting and what-if modeling solutions, surface insights at scale.
- Work in partnership with Finance colleagues, support their processes and teach them how to use various analytical tools to uplevel their work deliverables.
- Devise new or automate existing financial models and processes, statistical or driver-based forecasts and simulations, reporting and insights-gathering processes, and present technical analyses to technical and non-technical executive audience.