Senior Accountant II, AI Automation and Analytics Lead, Payroll Accounting at Google in Chicago, IL, USA

Job description

• Google accountants are a savvy bunch who handle the core accounting responsibilities at Google. You know your accounting principles and the full accounting process end to end. You'll advise on financial reports required by governmental regulations, and review, analyze, and interpret financial and budgetary reports. Every day is a new challenge, and you're continually looking for ways to help our team become more efficient and effective. A team player at heart, you collaborate with our global team, advocate best practices and pitch in where needed. You move fast while keeping your attention to detail, and you tap into your problem-solving skills to support business objectives.
• You'll lead an accounting process from end-to-end. Other responsibilities include reconciling balance sheets and P&L accounts, and providing supplementary financial information for internal and external reports.
• In this role, you will operate at the intersection of accounting domain expertise and data engineering. You will combine an automation and AI-first builder mindset with accounting fluency to modernize financial reporting architectures, eliminate manual data manipulation, and build scalable system solutions. Working cross-functionally with operational accounting teams, central engineering and the Data and AI teams. You will lead the evolution of our financial data infrastructure to deliver actionable, driver-based insights that satisfy our reporting deliverables and partner needs.
• 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: $157000 - $227000 (USD) + 20% bonus target + equity + benefits
• Learn more about benefits at Google.

Responsibilities

• Build and maintain automated data pipelines in partnership with Engineering and Data and Analytics (DnA) teams and relational data models connecting core accounting, payroll, and operational systems.
• Help to design, automate, and optimize calculation engines to streamline close processes and reduce cycle times.
• Transition prototype scripts and manual workflows into enterprise-grade, machine-deployed systems with data governance and auditability.
• Serve as the technical bridge between accounting domain leads and central engineering teams, translating business logic into technical requirements. Build automated, driver-based reporting models and AI-assisted workflows to deliver predictive and diagnostic insights.
• Mentor finance team members on SQL, modern automation tools, and troubleshooting to scale technical proficiency.

Requirements

• Bachelor's degree in Accounting or Finance, or equivalent practical experience.
• Certified Public Accountant (CPA) or Chartered Accountant (CA).
• 10 years of experience in accounting or a related function, or 8 years with an advanced degree in accounting, business, or finance.
• Experience in SQL, relational data modeling, and automated pipeline development.
• Experience applying AI/LLM tools, prompt engineering, or intelligent automation to finance workflows.
• Experience with Record-to-Report (R2R) accounting processes, General Ledger (GL) structures, accruals, and variance analysis.
• Demonstrated experience building driver-based variance bridges and upskilling finance colleagues in technical tools.
• Proven track record of replacing fragmented spreadsheets with scalable technical infrastructure and centralized data models.
• Strong background translating accounting requirements into technical architecture specifications for central data teams.

Skills

Required

• SQL
• Relational data modeling
• Automated pipeline development
• AI/LLM tools
• Prompt engineering
• Intelligent automation
• General Ledger (GL) structures
• Accruals
• Variance analysis

Preferred

• Driver-based variance bridges
• Technical upskilling
• Scalable technical infrastructure
• Centralized data models