Product Owner

Associa•Dallas, TX

11d

About The Position

We’re looking for a Product Owner who can operate inside complex, data-heavy environments and bring clarity to execution. This role sits at the intersection of data engineering, analytics, and customer-facing reporting. You’ll work closely with engineers, analysts, and stakeholders to define what needs to be built, structure the work, and ensure teams are consistently delivering against clear business outcomes. You will lead planning, backlog structure, and day-to-day execution. The goal is simple: teams should know exactly what to work on, why it matters, and how it connects to customer value. This is a hands-on product role focused on driving execution, clarity, and outcomes in a data-heavy environment.

Requirements

Ability to interview subject matter experts that drive insights for qualifying product work.
Experience owning backlog, epics, user stories, and roadmap
Strong execution in Agile environments (planning, refinement, delivery)
Ability to define success criteria and drive toward outcomes
Comfortable working with data pipelines and data movement concepts
Comfortable working with reporting tools (Power BI or similar)
SQL fundamentals (not required to code daily)
Experience working on data-heavy or analytics-driven products
Ability to take chaos and create structure
Strong problem-solving and prioritization skills
Comfortable working with engineering teams on technical topics
Strong communicator who can simplify complex ideas
Confident leading meetings and driving alignment
Able to challenge teams and keep work focused on value
Deep experience using Jira to manage real product delivery (2+ years minimum)
Experience structuring backlogs, linking dependencies and blockers while tracking progress

Nice To Haves

Data onboarding or migration
APIs and integrations
Enterprise systems

Responsibilities

Own epics, user stories, and backlog in Jira
Define priorities based on business impact and dependencies
Ensure all work is clearly scoped, sequenced, and ready for execution
Drive sprint planning, refinement, and demo readiness
Take unclear, messy inputs and turn them into structured work
Define “what done looks like” before work begins
Break down large efforts into sprint-sized deliverables
Prevent teams from over-engineering or drifting from value
Partner with data engineers working in environments like Databricks
Help shape data pipelines, transformations, and reporting outputs
Ensure data flows translate into usable dashboards and reports (Power BI)
Understand how data moves from source → pipeline → output
Act as the bridge between engineering and business stakeholders
Translate technical work into clear business outcomes
Ensure everyone understands what’s being built and why
Lead meetings and drive decisions without relying on senior escalation
Structure work around outcomes, not systems or components
Ensure stories are sized correctly and completed within a sprint
Manage dependencies across teams and systems
Introduce and refine processes when needed (e.g., business vs technical refinement)