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 in programming and SQL.
• Experience working with cross-functional teams, including engineering, product management, and business stakeholders.

Preferred qualifications:

• Experience working within Finance domains (e.g., accounting, financial planning and analysis, treasury, procure-to-pay).
• Experience in technical fluency and a comfort level with AI, enabling partnership with engineering teams.
• Track record of managing and delivering complex AI/ML or large-scale data projects.
• Understanding of data architecture, data warehousing, data governance, and business intelligence principles.
• Ability to influence without direct authority and drive consensus across executive stakeholders.
• Excellent problem-solving, and communication skills, with the ability to convey complex technical concepts to non-technical audiences.

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.

As a Program Manager on the Finance Data and Analytics (DnA) team, you will play a pivotal role in driving high-impact AI and data projects from initiation through to launch and landing. You will be the crucial link between Finance business stakeholders and various engineering teams (including DnA, FinEng, Cloud, and others). Your strong technical expertise and program management skills will be essential to ensure we design, build, and deliver innovative solutions that provide significant business value, are widely adopted, and can scale. You will be responsible for the how and when of project delivery, ensuring technical feasibility and orchestrating cross-functional execution.

The US base salary range for this full-time position is $148,000-$215,000 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

• Partner with Finance stakeholders, including Subject Matter Expert (SME) and process owners, to understand business challenges, processes, and opportunities for AI and data-driven solutions.
• Translate business needs into clear, feasible technical requirements, solution designs, and actionable project roadmaps, considering the key AI/ML capabilities.
• Define project scope, objectives, success metrics, and key features, prioritizing work to deliver iterative value, starting with minimum viable products.
• Exercise technical judgment to evaluate design choices, understand technical trade-offs, and ensure scalable, secure, and compliant solutions.
• Collaborate with virtual project teams composed of Developers (e.g., data scientists, software engineers, data engineers, BI analysts) from various internal and partner teams. Identify, analyze, and mitigate project risks and dependencies, remove blockers to ensure on-time delivery.