The Technical Product Owner will play a key role in the enterprise data division, focused on the successful delivery of data products for a healthcare payor organization. Partners with engineering, data science, and business teams to define and prioritize the data product roadmap. This role requires an outstanding combination of business insight, deep technical knowledge of data systems, and a passion for using data to solve complex healthcare challenges. Key Responsibilities Work with product management and business partners to define the vision, strategy, and roadmap for enterprise data products. Translate business needs and user insights into a clearly defined, prioritized, and well-groomed product backlog. Write and refine detailed user stories with clear acceptance criteria for both functional and non-functional requirements. Prioritize backlog items based on business value, technical feasibility, and consistency with the overall product strategy. Stakeholder Collaboration: Serve as the main liaison between technical data teams and various business units, including analytics, operations, and clinical teams. Communicate the vision, technical capabilities, and release plans of the data solution to both technical and non-technical audiences. Conduct stakeholder interviews and user reviews to gather feedback and refine product features. Agile and Delivery Management: Actively participate in agile ceremonies, including sprint planning, stand-ups, and retrospectives. Ensure the development team is accountable for delivering committed features on time and that the technical solution meets the business goal. Data Governance and Compliance: Collaborate with data governance teams to ensure all data handling aligns with regulations such as HIPAA and other privacy and security policies. Monitor data quality and integrity and drive remediation where needed. Assist in the documentation of the enterprise data dictionary and data lineage. Technical Acuity: Cultivate a deep understanding of data systems, data architecture, and modern data processing frameworks (e.g., ETL/ELT, data lakes). Have experience with technical concepts and the ability to query backend data systems using SQL to validate user stories and test results. Track product performance and team metrics to evaluate progress toward goals and identify opportunities for improvement. Data Operations or Data Transformation Focus: Data Operations: Specifically manage data ingestion, extraction, and sharing products. Work closely with data engineers to define requirements for data pipelines, APIs, and data delivery mechanisms. Data Transformation: Focus on data modeling and transformation products. Partner with data engineers and data scientists to build robust data models and ensure data is accurately transformed for analytics, reporting, and other enterprise needs.
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Job Type
Full-time
Career Level
Mid Level