Data Product Manager

Job Description

Job Description

Description:

At CSpring, we believe in the power of data to drive decisions and real-world impact. We’re a purpose-driven consulting firm specializing in data strategy, data engineering, and data analytics. Our clients span the public and private sectors, and our work helps them solve complex problems, gain insights, and achieve measurable results.

We're seeking talented professionals who are collaborative, curious, and committed to making a difference that thrive at the intersection of data, technology, and business strategy. Whether you're passionate about transforming public programs, enabling executive decision-making, or modernizing legacy systems, you'll find meaningful work and purpose here.

Why You’ll Love Working Here

• Purposeful Projects – Improve systems that serve real people by delivering smarter data, streamlined processes, and strategic insight.
• People-First Culture – We’re as committed to your growth as we are to delivering high-impact solutions. You’ll find support, autonomy, and community here.
• Strategic, Hands-On Work – From data architecture and documentation to client workshops and solution delivery, you’ll influence every step of the process.
• Collaborative Trust – Our clients rely on us to listen carefully, deliver consistently, and guide wisely. We partner with integrity, curiosity, and heart.

What You'll Do

You'll work with clients to turn their enterprise data vision into a defined, sequenced, and communicated plan of record:

• Own product definition for the data portfolio — reporting and analytics, privacy-by-design, segmentation, predictive models, and the platform capabilities underneath them.
• Maintain the roadmap: a rolling view of what the data team is delivering across the next two to three quarters, kept current, and defensible to any executive who asks why something sits where it does.
• Write the product vision documents, acceptance criteria, and release notes that let engineers build without guessing and let stakeholders know what they are getting.
• Define what success looks like for every product, instrument it, and report on it — usage, adoption by department, time to insight, model performance in production, and the business result it was built to move.
• Say plainly when something isn't working, and change or retire products that don't earn their usage.
• Run the planning and execution rhythm: monthly planning, standups, and the working agreements that keep a small senior team moving on a Kanban flow.
• Keep BAU visible and bounded so it doesn't quietly consume delivery capacity.
• Sit with every function that touches fan, revenue, or venue data, understand what each is trying to accomplish, translate that into data product requirements, and close the loop when something ships.
• Serve as the standing connection between the data team and the rest of the organization.
• Write status that executives can read in one pass, launch communications that drive adoption, and documentation that makes the portfolio legible to people who weren't in the room.

Requirements:

• Seven or more years in product management, with meaningful time on data, analytics, or platform products.
• Experience with a modern data stack, enough to hold a credible conversation with engineers about tradeoffs without needing to write the code.
• Demonstrated ability to run planning and delivery for a technical team, and a track record of setting and reporting on product metrics rather than tracking output.
• Strong written communication, specifically the ability to write for executives.
• Working fluency with AI tooling in daily practice.
• A track record of taking data products from vision to adoption.

Bonus Experience

• Sports, entertainment, media, or consumer businesses with large customer bases.
• Defining AI-enabled product capabilities — conversational access to data, agent-driven insight delivery, or models embedded in business workflow.
• Privacy-by-design or data governance as part of a product you owned.
• Customer segmentation or predictive models.
• Kanban delivery with a monthly planning cadence.

If you've taken data products from a vision document all the way to people actually using them, we'd like to talk. Apply today!