Lead Product Manager, Data Engineering - Remote

Overview

We are looking for a Lead Product Manager to take ownership of our data products at FiscalNote. With the developments in AI how data is acquired and what value can be created with the data has changed. There are more opportunities to acquire data more efficiently and more ways to create customer value with it. You will play a crucial role in transforming our data operations, aligning our data acquisition roadmap with the overarching product vision, and advocating for the strategic use of data to enhance user experience.

In Short

• Understand the customer: conduct customer and stakeholder interviews to understand motivations, needs, and strategic data opportunities.
• Align and manage the company’s data acquisition roadmap to meet our overall product vision.
• Facilitate a two-way street with application development teams, identifying and advocating for data sets valuable to customers.
• Make good use of AI to create efficiencies and deliver value to customers.
• Evaluate, select, and manage third-party vendors for data acquisition and integration projects.
• Monitor and communicate project progress, risks, and blockers to senior leadership.

Requirements

• 5+ years of technical product management experience, preferably with data and AI product ownership.
• Proven success in managing complex, multi-stakeholder projects from conception to delivery.
• Strong collaboration and communication skills with technical and business partners.
• Experience in evaluating and integrating external data vendors and sources with technical literacy in data engineering.
• Demonstrated ability to set priorities, make tradeoffs, and focus teams on high-value outcomes.
• Ability to prototype in Figma or code to demonstrate potential data-driven value for clients.
• Client-focused approach, understanding data needs and connection with client objectives.
• Willingness to learn about policy with the ability to interface effectively between engineers and business teams.

Benefits

• Engaged and collaborative work environment.
• Opportunity to work on innovative data products.
• Professional development opportunities.
• Impactful role in shaping the future of data operations.