Staff Product Owner - GM Motorsports

GM • Austin, TX

7d • Hybrid

About The Position

The Staff Product Owner leads product strategy, roadmap development, and delivery execution for GM Motorsports data and analytics products supporting Strategy, Vehicle Performance, and Competition Engineering across NASCAR, IndyCar, and other GM racing programs. The role combines product ownership and scrum leadership, partnering with motorsports stakeholders and leading cross-functional delivery across data science and data engineering teams. Direct motorsports experience is not required; success depends on understanding stakeholder needs, translating them into roadmaps and backlog items, and driving high-quality, timely delivery in a complex, fast-paced environment.

The position serves as the accountable Product Owner for the teams, owns product vision and priorities, and facilitates agile practices. It partners with business and technical stakeholders to define feasible solutions, manage dependencies and trade-offs, communicate status and recommendations to senior leaders, and measure outcomes through KPIs and adoption metrics. The Staff Product Owner also advises stakeholders on data and AI capabilities, models GM Behaviors, and informally mentors colleagues while helping improve product and agile practices.

The role is categorized as hybrid. The selected candidate is expected to report to a specific location at least three times a week or at another frequency set by their manager. Relocation benefits are available to candidates who qualify under company policy. GM does not provide immigration-related sponsorship for this role.

Requirements

• Bachelor’s degree in Engineering, Computer Science, Data/Analytics, Business, or a related field, or equivalent experience.
• At least 8 years of experience as a product manager, product owner, business analyst, systems analyst, or in a similar role.
• Significant product management or product ownership experience, including defining product vision and multi-release roadmaps, managing complex backlogs across stakeholder groups, and delivering digital or data products in an agile environment.
• Experience serving as a Product Owner and/or scrum lead for one or more agile teams, such as data, analytics, or software teams.
• Ability to work cross-functionally and influence without formal authority, partnering with technical and non-technical stakeholders at multiple levels.
• Strong communication skills, including presenting concise, data-informed recommendations to senior leadership, translating technical concepts for non-technical stakeholders, and giving actionable guidance to development teams.
• Familiarity with data science and data engineering concepts, including analytics use cases, data pipelines, model development and deployment, and experimentation, sufficient to ask informed questions, understand trade-offs, and make prioritization decisions.
• Ability to solve complex or new problems using deep experience and strategic thinking, lead large or high-visibility cross-functional initiatives, mentor less-experienced colleagues, and elevate team practices.
• Must not require GM immigration sponsorship now or in the future, including sponsorship or other immigration support for work authorization.

Nice To Haves

• Experience owning data-heavy products or platforms in partnership with data science or data engineering teams, including defining SLAs, data contracts, and quality expectations for downstream consumers.
• Familiarity with modern data and analytics technology stacks, including cloud platforms such as Azure; tools such as Databricks and Spark; modern data pipelines; and streaming technologies such as Kafka.
• Familiarity with analytics, BI, experimentation, and ML platforms.
• Understanding of modern data engineering patterns, including data lakes or lakehouses, batch and streaming pipelines, warehousing, orchestration, and observability, with the ability to discuss trade-offs with engineers.
• Ability to read and reason about technical designs, such as high-level schemas, pipeline diagrams, and architectural decisions, and use that understanding to prioritize work without implementing code hands-on.
• Product ownership experience in an engineering-heavy domain such as automotive, mobility, manufacturing, motorsports, or aerospace, including defining and tracking data or analytics product KPIs and success metrics.
• Formal agile training or certifications such as CSPO, PSPO, or Scrum Master, and experience tailoring agile practices to complex, multi-team environments.
• Ability to navigate enterprise processes, governance, and risk while maintaining urgency and forward progress.

Responsibilities

• Serve as the accountable Product Owner for cross-functional data science and data engineering teams supporting GM Motorsports.
• Own and maintain product vision, roadmaps, and prioritized backlogs for motorsports analytics and data products, aligned with business strategy and measurable outcomes.
• Act as scrum lead for both teams by facilitating and improving backlog refinement, sprint planning, sprint reviews, and retrospectives.
• Ensure user stories and acceptance criteria are clear and well defined, remove impediments, and protect the teams’ ability to execute.
• Partner with motorsport Strategy, Vehicle Performance, and Competition Engineering stakeholders to understand objectives, workflows, and decision-making needs.
• Translate complex requirements into implementable features and experiments, and recommend sequencing and trade-offs based on scope, risk, and downstream impacts.
• Collaborate with data scientists, data engineers, architects, and product partners to define feasible, scalable solutions aligned with enterprise data and AI standards.
• Drive cross-functional alignment across motorsport engineering, IT, security, operations, and other groups; identify and manage dependencies.
• Communicate product strategy, priorities, risks, and status, including concise, insights-driven updates and recommendations to senior and executive leadership.
• Provide delivery teams with clear context, rationale, and direction.
• Define and track product KPIs and adoption metrics, using data and stakeholder feedback to iterate on roadmap and backlog priorities.
• Help stakeholders understand the capabilities of modern data science and data engineering platforms.
• Model and reinforce GM Behaviors in day-to-day work and team interactions.
• Provide informal leadership and mentoring to product owners, analysts, and team members, and contribute to improving product and agile practices.

Benefits

• Relocation benefits are available for candidates who qualify under company policy.
• GM describes benefits and well-being support through its Total Rewards resources.

What This Job Offers

• Job Type: Full-time
• Career Level: Senior