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Talkiatry is seeking a Senior Data Product Manager to own the evolution of its data stack, end-user data enablement strategy, and third-party integrations. This role spans nearly every part of Talkiatry's operations, requiring balance between day-to-day execution and strategic vision for data capabilities.
You will partner closely with Referrals, Operations, Marketing, Finance, Engineering, and Product teams to identify high-impact opportunities and deliver scalable solutions across the data ecosystem. Key responsibilities include: leading product strategy and execution for the data platform and integrations; developing and maintaining long-term roadmaps for the data stack, metrics layers, and proprietary data models; owning third-party integrations across referrals, billing, marketing, and clinical systems; ensuring data quality and reliability through validation, monitoring, and alerting; identifying where AI and automation add value for end users; and putting analytics, attribution, and segmentation directly in the hands of non-technical teams without engineering dependencies.
You will balance short-term operational priorities with long-term platform investments, lead cross-functional collaboration on complex initiatives, anticipate dependencies across interconnected systems, and define success metrics to evaluate product impact. The role requires navigating ambiguity by breaking down complex operational and systems challenges into actionable product opportunities.
Required qualifications include 4+ years of product management experience with 2+ years focused on data platforms, data products, or data infrastructure. You must have working fluency with the modern data stack (ELT, cloud warehousing, transformation, orchestration, BI, semantic layers, reverse ETL), comfort reading and writing SQL, and ability to reason independently about data grain, joins, duplication, and completeness. You should have experience leading complex product initiatives across multiple teams, owning metric definitions and governance, building self-serve data capabilities for non-technical teams, and developing product strategy with strong prioritization and execution skills. Familiarity with AI concepts, technologies, and practical applications is essential, along with strong product judgment and excellent communication skills.
