Data Product Owner

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Job Description:

Summary

The Data Product Owner role owns the end-to-end delivery of data as a product—partnering with customers and internal teams to define a market-leading data offering, translate needs into clear requirements, and ensure
high-quality, secure, and scalable data products.

Essential Functions

• Monitor internal processes and product performance using Power BI dashboards, KPIs, and data quality signals; identify issues and drive corrective actions.
• Own the data product roadmap and backlog: define epics, write user stories with acceptance criteria, and prioritize delivery based on customer value, risk, and feasibility.
• Develop a strategic plan to evolve current data capabilities into a market-leading data product (e.g., data access, packaging, governance, pricing/entitlements, and customer experience).
• Drive requirements with the established enterprise IT data management team to access, model, and transform data (e.g., in Snowflake) into customer-ready insights and products.
• Partner with IT Data and AI teams to expose data to customers safely and effectively, including enabling data for GenAI and ML use cases.
• Assess customer needs for data and access to data through discovery, interviews, and feedback loops; translate needs into API, dataset, and analytics requirements.
• Develop and operationalize machine learning models that support fleet managers in daily operations (e.g., predictions, anomaly detection, recommendations), collaborating with IT data science and engineering.
• Define and maintain product metrics (adoption, latency, freshness, accuracy, SLAs) and establish ongoing observability for data pipelines and APIs.
• Collaborate cross-functionally with IT engineering, analytics, security, legal/compliance, and customer teams to deliver secure, reliable, and scalable data products.

Additional Responsibilities

• Perform other duties as assigned

Skills and Abilities

• Demonstrated ability to run customer discovery and translate needs into technical requirements, user stories, and measurable outcomes., Required
• Hands-on experience with Power BI (or similar) for KPI definition, dashboarding, and performance monitoring., Required
• Experience visualizing data and communicating insights to both technical and non-technical stakeholders., Required
• Excellent communication, stakeholder management, and ability to drive decisions in ambiguous, cross-functional environments., Required
• Experience with data product governance (data contracts, catalog/lineage, quality rules, entitlement models, privacy-by-design)., Preferred
• Experience in logistics, fleet management, telematics, or operational analytics., Preferred

Qualifications

• Bachelor's Degree in Bachelor’s degree in Computer Science, Information Systems, Data Science, Engineering, or related field (or equivalent experience)., Required
• 3 years or more in Experience in product ownership/management, technical program management, or analytics roles delivering data platforms, data products, or API-enabled capabilities., Required
• Strong working knowledge of cloud data warehousing and analytics patterns; experience with Snowflake preferred. Expert, Required
• Understanding of APIs (REST concepts, authentication/authorization, versioning) and how customers consume data products programmatically. Advanced, Required
• Familiarity with machine learning concepts and lifecycle (feature definition, evaluation metrics, monitoring/drift) and partnering with data science teams to deliver ML-enabled products. Advanced, Required
• Familiarity with ML Ops practices (model deployment, monitoring, drift detection) and experimentation/A-B testing. Intermediate, Preferred
• Working knowledge of agile practices and tools (e.g., Scrum/Kanban; Jira/Azure DevOps). Intermediate, Preferred
• Certified Scrum Product Owner (CSPO), Preferred
• Microsoft Certified: Power BI Data Analyst Associate (PL-300), Preferred
• Snowflake SnowPro Core Certification, Preferred

Travel

• Yes, 1-10%

Job Category

Product Development

Compensation Information:

The compensation offered to a candidate may be influenced by a variety of factors, including the candidate’s relevant experience; education, including relevant degrees or certifications; work locati