Lead Product Manager, Finance Data Platform

About the Role

The FinTech team builds the platforms and systems that ensure every dollar transacted across Uber's global marketplace is accurately calculated, allocated, and reported. Our core mission is to provide a single, reliable source of truth for all financial data, enabling strategic decision-making at every level of the company.

The Finance Data Store (FDS) team, a key pillar within FinTech, owns the data warehouse that serves as the definitive source of financial truth for Uber's entire business. Our stakeholders are not just in finance; data scientists, pricing teams, and business leaders across the company rely on the integrity and availability of our data.

As the Lead Product Manager for the Finance Data Platform (FDS), you will own the product vision and roadmap for Uber's most critical financial data asset. You will be at the center of how Uber understands its own financial performance. In this role, you will work closely with partners in Data Science, Engineering, and Strategic Finance (StratFin) to ensure our data is accurate, scalable, and insightful.

Uber operates in a constantly-evolving and competitive environment. Quantifying our success depends on deeply understanding the financial context of every transaction and business decision. Doing this well at Uber’s global scale is a complex and fascinating problem with a direct impact on our P&L. You will apply your expertise in data platforms, financial systems, and business strategy to enhance our core data warehouse, develop new machine learning-powered predictive forecasts, and expose our rich data to the next generation of generative AI agents.

You will lead with a deep obsession for data integrity and rely on rigorous analysis and user research to make informed decisions with solid product instincts.

What the Candidate Will Do

• Drive the product roadmap for Uber’s core financial data platform (FDS), ensuring it meets the complex needs of finance, accounting, and data science stakeholders across the company.
• Collaborate and partner with dedicated Engineering and Data Science teams to drive innovation in financial data modeling, allocation accuracy, and system performance.
• Define the product strategy for new machine learning initiatives, such as developing predictive financial forecasts using the rich historical data within FDS.
• Pioneer new ways to surface financial data by creating secure, reliable, and well-documented interfaces for generative AI agents, like FinTech’s internally built Finch Data Agent, to consume and reason over FDS data.
• Effectively present and communicate your strategy, roadmap, and growth plans to a wide range of stakeholders, from business analysts to senior finance and engineering leadership.
• Own and evangelize the product vision and strategy, effectively communicating the 'why' to inspire and align cross-functional teams and leadership, and translating that vision into a concrete, actionable roadmap.
• Serve as the ultimate owner of financial data integrity, partnering closely with Operations (Ops), Pricing, StratFin, and Accounting to conduct deep-dive analyses that ensure our data models accurately reflect the complex operational realities of Uber's business.

Basic Qualifications

• Product Experience: Minimum of 6 years of experience in Product Management demonstrating product thinking and delivering successful and innovative data products or platforms.
• Leadership Experience: Prior experience leading cross-functional teams and creating/implementing coherent product visions, multi-year strategies, and roadmaps.
• Results Oriented: You create clear definitions of success and guide prioritization and ideation against that. Passionate about delivering outcomes, not just features.

Preferred Qualifications

• Analytical Experience: Deep understanding of data warehousing, data modeling, ETL processes, and large-scale data systems. Experience with machine learning models and AI technologies is strongly preferred.
• Strong Business & Financial Sense: A strong understanding of corporate finance, FP&A, and accounting principles. You can translate complex business requirements into a technical product strategy that delivers accurate and reliable financial data.
• Communication & Partnership Skills: Prior experience collaborating with and influencing highly technical data science and engineering teams alongside demanding finance stakeholders.
• Academic background or equivalent work experience in data science, statistics, accounting, finance, or engineering highly preferred.

For San Francisco, CA-based roles: The base salary range for this role is USD$216,000 per year - USD$240,000 per year.

You will be eligible to participate in Uber's bonus program, and may be offered an equity award & other types of comp. You will also be eligible for various benefits. More details can be found at the following link .

Uber's mission is to reimagine the way the world moves for the better. Here, bold ideas create real-world impact, challenges drive growth, and speed fuels progress. What moves us, moves the world - let's move it forward, together.

Uber is proud to be an Equal Opportunity employer. All qualified applicants will receive consideration for employment without regard to sex, gender identity, sexual orientation, race, color, religion, national origin, disability, protected Veteran status, age, or any other characteristic protected by law. We also consider qualified applicants regardless of criminal histories, consistent with legal requirements. If you have a disability or special need that requires accommodation, please let us know by completing this form .

Offices continue to be central to collaboration and Uber's cultural identity. Unless formally approved to work fully remotely, Uber expects employees to spend at least half of their work time in their assigned office. For certain roles, such as those based at green-light hubs, employees are expected to be in-office for 100% of their time. Please speak with your recruiter to better understand in-office expectations for this role.