Senior Technical Product Owner - EDW/AI

Location: Dayton, OH preferred; Cincinnati/Columbus area considered Hybrid: Minimum weekly onsite participation Initial Business Focus: Insurance Pay Rate Range: $60-70/hr, We are seeking a hands-on Senior Technical Product Owner / Business Systems Analyst to support a large-scale enterprise data platform that ingests, manages, transforms, and delivers data to internal products and business teams.

This role will serve as the primary bridge between internal Product teams and Data Engineering. Many incoming requests begin as high-level business needs without sufficient clarity around required datasets, expected data behavior, processing requirements, acceptance criteria, or realistic delivery scope. This individual will own the discovery and refinement process so engineering receives well-defined, appropriately prioritized work.

This is not a software development position or a high-level product strategy role. The ideal candidate combines strong Product Owner ownership with hands-on Business Analysis capabilities and enough enterprise data-platform knowledge to challenge incomplete or unrealistic requirements.

Key Responsibilities Product Intake & Requirements Serve as the primary intake point for new products, features, enhancements, and functional issues. Lead discovery sessions directly with internal Product stakeholders. Determine what a stakeholder is trying to accomplish, what data is required, how it will be consumed, and what constitutes a successful outcome. Identify missing requirements and push back when a request is not sufficiently defined for engineering. Translate ambiguous requests into detailed functional specifications, business rules, representative examples, edge cases, and acceptance criteria. Capture requirements involving data ingestion, transformations, updates, deletions, retention/TTL, data quality, reconciliation, and downstream delivery. Ensure expectations for data quality and upstream/downstream responsibilities are explicitly defined. Data Platform Requirements Apply strong conceptual knowledge of enterprise data processing and data movement. Understand how differences in volume, frequency, processing time, retention, and downstream use can materially affect requirements. Recognize when requests require deeper technical feasibility assessment from engineering.

Understand concepts such as

ETL/ELT and data ingestion Data warehousing and large-scale data processing Full versus incremental loads Data quality and reconciliation Data modeling/entity relationships Data retention and deletion Source-to-target requirements Downstream consumption/extraction Perform lightweight functional validation to ensure delivered data and functionality align with agreed requirements. Backlog & Delivery Ownership Own and maintain a prioritized product backlog. Partner with the Hiring Manager and Project Manager to balance customer demand, technical dependencies, engineering capacity, and business priority. Break large requests into smaller, achievable increments rather than treating every request as an all-or-nothing deliverable. Help establish realistic expectations around what can be delivered across near- and medium-term timelines. Work closely with engineering during collaborative inception/mob-style sessions. Remain involved throughout execution to answer functional questions and resolve requirement gaps. Coordinate UAT and stakeholder validation as appropriate. Process & AI-Assisted Delivery Help establish scalable Product intake, documentation, prioritization, and requirements standards for a growing product function. Use tools such as Microsoft Copilot and other approved generative AI tools to accelerate requirements analysis, specification development, gap identification, and acceptance-criteria creation. Critically validate AI-generated specifications rather than accepting generated output at face value. Operate effectively within collaborative, increasingly specification-driven engineering practices.

6+ years of relevant Product Owner, Technical BA/BSA, Data Product, or comparable enterprise delivery experience. Enterprise data-platform experience is required. Strong hands-on requirements elicitation, documentation, and functional specification experience. Experience personally turning vague stakeholder requests into engineering-ready requirements. Working knowledge of ETL/ELT, data ingestion, large-scale data processing, data warehousing, and downstream data delivery. Understanding of data quality, reconciliation, data mapping/modeling concepts, and functional data validation. Experience owning or influencing backlog prioritization across competing stakeholders. Comfortable challenging unrealistic or incomplete stakeholder requests. Experience working directly with software/data engineering teams. Strong stakeholder management and communication skills. Comfortable using generative AI as part of professional/product workflows. Azure Cosmos DB or comparable NoSQL/data-platform exposure. Azure Data Lake or broader Azure data ecosystem experience. Basic SQL/data-inspection capability. Experience with entity data, identity resolution, MDM, or complex enterprise data models. Insurance or another highly data-intensive industry. JIRA/Confluence. Collaborative inception, mob-working, or specification-driven development experience. Advanced use of AI for specification generation or requirements gap analysis.