Senior Product Manager

PowerPlan•Atlanta, GA

22d•Hybrid

About The Position

This is a highly strategic technical role on the Platform Team, leading the transition and development of PowerPlan's common cloud platform, NXT, and its shared capabilities. The person will help set the long-term data strategy for PowerPlan's Data Hub product and the platform's data access strategy as a whole. The person in this role will own the technical direction of Data Hub and shape how data flows across every NXT product — including how that data gets prepared and positioned for emerging AI-driven use cases — while additional platform capabilities like APIs, adapters, reporting, and security layers remain part of the portfolio as supporting infrastructure. Leadership will hand this person an initial vision to execute against, with the expectation that they develop and champion their own point of view on the platform's direction over time. This is not a strategy-and-marketing role that sits apart from delivery: the person will be embedded directly with the Scrum team's daily standups, sprint ceremonies, and ongoing refinement, while also fielding customer calls during research and handling escalations when a project or production customer needs product involved. Success here depends on close, day-to-day collaboration with Development Leads, Architects, Design, and the Services and Operations teams, and on staying current with how AI is reshaping both product data needs and the practice of product management itself. Our company builds a SaaS platform that helps enterprise finance, tax, and asset management teams manage complex regulatory and accounting requirements, and is now transitioning that core platform to the cloud through the NXT initiative. The Platform Team sits at the center of that transition, building the shared components, APIs, and data infrastructure that every other product team depends on, and does so through tight, ongoing collaboration across engineering, architecture, design, and operations. As AI becomes central to how customers use and act on their data, this team is also shaping how the platform prepares and exposes data for AI-driven consumption. It's an environment where deep technical ownership and cross-functional relationships go hand in hand, especially as the product suite scales.

Requirements

7-10 years of enterprise software product management experience, with a track record of increasing responsibility
Proven experience owning Data Hub or comparable core data infrastructure, including technical improvement planning in partnership with Development, Cloud, and Architecture
Real, hands-on experience with big data tooling — Databricks or equivalent — and modern data architecture, with comfort positioning data for AI-driven and machine learning use cases
Comfort using AI tools in your own product management practice — research synthesis, competitive analysis, roadmap drafting — and staying current on how AI is reshaping the discipline.
Experience driving requirements and planning for shared platform capabilities — APIs, adapters, and reporting or security layers — used across multiple product teams, and documenting decisions so they're repeatable.
Comfort operating at a strategic, trusted-advisor level with leadership while also staying hands-on with execution.
Comfort operating within a Scrum framework — daily standups, sprint ceremonies, and ongoing refinement — as a normal part of the role.
Comfort fielding customer calls for discovery and production escalations when a project or customer needs product involved, not just setting strategy from a distance.
Strong cross-functional collaboration skills, with experience partnering closely with Development, Architecture, Design, Cloud, and Services/Operations teams.
A former software engineer or cloud engineer background is a real plus — hands-on experience writing code or running cloud systems, not just familiarity with engineering concepts.
Excellent, persuasive written and verbal communication, including the executive presence to represent platform strategy to leadership.

Responsibilities

Takes on long-term product ownership of Data Hub — PowerPlan's core data product — building a technical roadmap in the first 30-90 days in consultation with Development, Cloud, and Architecture, and carrying that roadmap forward into ongoing platform optimization and scaling as Data Hub takes on a larger role across NXT.
Establishes Data Hub as a durable, forward-looking foundation for the platform's data layer, reducing risk as usage and scale grow. Reframes the data layer itself as a customer-facing value-add that enables reporting, analytics, and AI-driven use cases.
Builds and owns the technical roadmap for Data Hub in partnership with Development, Cloud, and Architecture leads, prioritizes investment against optimization and scaling needs as adoption grows, manages dependencies across simultaneous roadmap efforts, stays embedded in the Scrum team's daily standups and sprint ceremonies as a working participant, and takes point on escalations from active projects or production customers when product needs to get involved.
Defines and drives product requirements, planning, and UX decisions for the NXT platform's shared capabilities — including APIs, adapters, and reporting and security layers — so other product teams build on a common foundation instead of duplicating work, and documents the rationale behind these decisions so they're repeatable and trackable across teams.
Reduces duplicate engineering effort across product teams, keeps decisions maintainable for both internal engineering and customer-facing operations, and gives impacted teams a reliable, repeatable reference.
Provides customers a consistent, integrated user experience, and makes it easier for customers to access data in the platform.
Partners with Development Leads, Architects, and Design to evaluate build-versus-reuse tradeoffs for each shared component, and defines policies for tracking decisions and communicating them to impacted teams and manages dependencies across simultaneous shared projects which may have competing priorities.
Defines how platform data — including Data Hub and beyond — is structured and exposed to support emerging AI-driven use cases across PowerPlan's products, using hands-on big-data tooling such as Databricks to make that readiness real rather than theoretical.
Positions PowerPlan's data layer as a forward-looking, AI-ready foundation rather than a constraint, ahead of customer and market expectations for AI-driven data use.
Works with Development, Cloud, and Architecture to assess current data structures against AI and machine learning consumption needs, applies hands-on experience with Databricks or equivalent big-data tooling and modern data architecture, and partners with Data Hub and platform teams to close gaps.
Uses AI tools to speed up research, roadmap work, and product reviews in coordination with how AI is used across our software development lifecycle, and stays current on how AI is reshaping the product management and engineering disciplines.
Improves the speed and quality of this person's own product decisions, and models a practice other product managers can adopt as AI tooling matures.
Incorporates AI tools into day-to-day product management workflows — research synthesis, competitive analysis, roadmap drafting, and reviewing engineering output. Continuously evaluates new AI-driven product management and engineering practices as they emerge.
Identifies new product opportunities for NXT expansion, with a primary lens on improving platform data access, informed by customer and industry research and by emerging AI-driven data use cases.
Gives customers easier, more unified access to their data across the NXT platform, and builds a pipeline of expansion opportunities rooted in real data-access needs — including AI-driven ones — rather than ad hoc feature ideas.
Leads and participates in customer and industry research to surface platform data-access gaps, works with Development and Architecture to scope how new capabilities would fit the platform, and brings forward NXT expansion opportunities with a lighter-weight business case rather than full market sizing and revenue forecasting.