Job description

Position Summary Level Access is seeking a Data Product Manager to own enterprise data products that power reporting, analytics, operational intelligence, and AI-enabled workflows across the business. Reporting to the Sr. Director of Business Systems, this role bridges business stakeholders and the Data & AI Engineering team to translate business problems into trusted data products, reusable context, analytics capabilities, and AI-ready solutions. Success in this role is measured not by data delivered, but by business outcomes enabled. Responsibilities Own the Data Product Roadmap Partner with business leaders to identify high-value data, analytics, automation, and AI opportunities. Translate business objectives into a prioritized roadmap of reusable data products and capabilities. Prioritize work based on business impact, operational efficiency, customer outcomes, AI readiness, and strategic goals. Define success measures that connect data product delivery to business outcomes. Define Trusted Data Domains Define enterprise data domains, ownership models, business definitions, metrics, KPIs, and data contracts. Maintain the enterprise data dictionary and business glossary. Drive consistency across reporting, dashboards, operational systems, and AI-enabled workflows. Advocate for data quality, lineage, governance, stewardship, and appropriate use of sensitive data. Drive AI-Augmented Product Development Use rapid experimentation, AI-assisted prototyping, and iterative validation to shape data and AI product opportunities. Translate business problems, signals, and data opportunities into clear product specifications for Data Engineering, Applied AI Engineering, Business Systems, and other technical teams. Use AI tools to accelerate discovery, synthesis, requirements development, prototype generation, documentation, and decision support. Help establish a prototype-to-spec workflow that turns validated ideas into actionable work for AI-augmented engineering teams. Partner with Engineering in an AI-Augmented Delivery Model Work as part of a small cross-functional Data & AI Product Team that collaborates early and often across product, data, AI, business systems, and engineering disciplines. Partner with Data Engineers and Applied AI Engineers on solution design, prototype review, specification refinement, validation, testing, instrumentation, and adoption planning. Ensure technical solutions align with business intent, data requirements, technical feasibility, governance expectations, and measurable outcomes. Support an AI-augmented SDLC where specifications, test cases, implementation guidance, and documentation may be accelerated with AI and validated by human expertise. Qualifications Required 5+ years of experience in Product Management, Data Product Management, Business Systems, Analytics, or a related discipline. Experience working with senior business stakeholders to define priorities, requirements, tradeoffs, and success measures. Experience supporting AI, machine learning, copilots, agentic workflows, or intelligent automation. Strong understanding of data platforms, reporting, BI, analytics, data governance, and enterprise data concepts. Experience translating business needs into product specifications, technical requirements, user stories, acceptance criteria, and measurable outcomes. Experience working in highly collaborative product and engineering environments that use rapid prototyping, iterative discovery, and early technical partnership. Strong communication, facilitation, and stakeholder management skills. Preferred Familiarity with AI-assisted product workflows, rapid prototyping, prompt-based experimentation, or AI-generated specification and documentation approaches. Experience with modern data platforms such as Databricks, Snowflake, Microsoft Fabric, or equivalent. Exposure to enterprise SaaS business models and operational metrics. Key Success Measures Increased adoption of trusted enterprise data products. Faster delivery of reporting, analytics, business insights, and AI-enabled workflows. Improved data quality, trust, governance, and reuse across the organization. Demonstrable business impact from data and AI investments. Application Process If you thrive in a fast paced environment and you are eager to make a significant impact in the field of accessibility, we would love to hear from you! Interested in immediate consideration? Please submit your resume to be considered for this role. The anticipated application window is 40 days from the date job is posted. However, factors such as candidate flow and business necessity may require us to shorten or extend the application window. This position is a current open vacancy. Candidates who are selected for an interview will be notified of the hiring decision within 45 days following their final interview. Level Access is committed to workforce diversity and is an Equal Opportunity Employer. We are dedicated to providing reasonable accommodations throughout the hiring process. Level Access uses artificial intelligence (AI) tools to support and enhance our recruitment and hiring processes. These tools may assist with activities such as résumé screening, skills assessments, interview scheduling, and communication These tools are designed to assist our recruiters and do not make final hiring decisions. All AI-assisted processes are subject to human review and candidate information is handled in accordance with our Privacy Policy and applicable regulations. To learn more about how we collect and use personal data, please review our Privacy Statement ( levelaccess.com ) and our Trust Center ( trust.levelaccess.com ). Compensation and Benefits This is a full time position. The annual base salary hiring range for this position is $92,000 - $100,000 for employees located in the United States and CA$86,000 - CA$130,000 for employees located in Canada. The salary range reflects expected base pay for this role at the time of posting. The compensation package offered will be determined by factors such as demonstrated experience, skills, and internal equity. Expected base pay hiring ranges for candidates outside of the United States and Canada will be reviewed during the interview process, if selected. This position is eligible for incentive compensation in the form of a company bonus plan. Level Access is committed to supporting our global team with comprehensive and inclusive benefits. For employees in the United States and Canada, our offerings include medical, dental, and vision insurance, life and disability coverage (STD/LTD), and a retirement match. We also prioritize well-being and growth through flexible paid time off, paid parental leave, a remote work stipend, and professional development reimbursement. For employees in other locations, benefits are tailored to local regulations and employment status to ensure competitive support worldwide.

Requirements

Must-haves

Level Access is seeking a Data Product Manager to own enterprise data products that power reporting, analytics, operational intelligence, and AI-enabled workflows across the business.
Success in this role is measured not by data delivered, but by business outcomes enabled.
Own the Data Product Roadmap
Partner with business leaders to identify high-value data, analytics, automation, and AI opportunities.
Translate business objectives into a prioritized roadmap of reusable data products and capabilities.
Prioritize work based on business impact, operational efficiency, customer outcomes, AI readiness, and strategic goals.
Define success measures that connect data product delivery to business outcomes.
Define Trusted Data Domains
Define enterprise data domains, ownership models, business definitions, metrics, KPIs, and data contracts.
Maintain the enterprise data dictionary and business glossary.
Drive consistency across reporting, dashboards, operational systems, and AI-enabled workflows.
Advocate for data quality, lineage, governance, stewardship, and appropriate use of sensitive data.
Drive AI-Augmented Product Development
Use rapid experimentation, AI-assisted prototyping, and iterative validation to shape data and AI product opportunities.
Translate business problems, signals, and data opportunities into clear product specifications for Data Engineering, Applied AI Engineering, Business Systems, and other technical teams.
Use AI tools to accelerate discovery, synthesis, requirements development, prototype generation, documentation, and decision support.

Nice-to-haves

Familiarity with AI-assisted product workflows, rapid prototyping, prompt-based experimentation, or AI-generated specification and documentation approaches.
Experience with modern data platforms such as Databricks, Snowflake, Microsoft Fabric, or equivalent.
Exposure to enterprise SaaS business models and operational metrics.
Key Success Measures
Increased adoption of trusted enterprise data products.
Faster delivery of reporting, analytics, business insights, and AI-enabled workflows.
Improved data quality, trust, governance, and reuse across the organization.
Demonstrable business impact from data and AI investments.

Application prep

Use the role’s language and application details while tailoring your materials.

Keywords to mirror

aimachine learningaccessibility

Platform: greenhouse
Effort: quick

Benefits

Benefits detected in the listing.

Dental

Vision

Paid Time Off

Parental Leave

Professional Development