Senior Product Manager, Iterable

• 5+ years of product management experience in B2B SaaS, focused on backend, platform, or data infrastructure products
• Hands-on experience with user and event data systems—for example: ingestion pipelines, identity/alias models, event stores, or large search/document databases (e.g., Elasticsearch)
• Strong instincts around APIs and schemas: you’re comfortable reading JSON payloads, thinking through nesting vs. flattening, and managing breaking changes over time
• Familiarity with distributed systems and data infra (Kafka/Pulsar, Redis, relational or NoSQL stores, or search engines) and the tradeoffs around performance, reliability, and cost
• Experience collaborating with AI/ML or data science teams on the data side—feature availability, data quality, semantics—enough to know what really blocks good models and agent behavior
• Strong analytical skills (including SQL) and a habit of using data to drive prioritization and validate impact
• Clear, direct communication; you can explain a data or infra decision to both senior engineers and non-technical stakeholders without jargon for its own sake

Desirable

• We are looking for a Senior Product Manager to define how data moves, lives, and performs across Iterable. You’ll own the vision and roadmap for the full lifecycle of user and event data, from ingestion to intelligent storage to governed, high-performance access
• You’ll shape the systems that power both messaging surfaces and Nova AI experiences, ensuring data is fast, reliable, and ready for real-time decisioning
• Every campaign launched, every journey orchestrated, every model activated, it all depends on the foundations you build
• Own the end-to-end user data platform charter: define how user and event data moves from APIs and pipelines into storage, through schema and lifecycle management, and out through query surfaces used by sends, journeys, and AI features—staying focused on core user data infrastructure, not analytics UI or external integrations
• Make ingestion and identity reliable at scale: evolve ingestion APIs and pipelines with clear SLOs, prioritization, and fair-usage limits, and drive a clear identity model so we can safely move users from anonymous to known without duplicates or data loss
• Modernize storage, schemas, and guardrails: lead ES8 and user-store roadmaps, retention and cost work, and turn schema management into a first-class product (field removal, usage heatmaps, structural guardrails) so customers can keep only the data that matters
• Enable Nova and product teams with better data: partner with AI/ML and application teams to define what “AI-ready” means, evolve a centralized query layer with guardrails, and own platform metrics (SLOs, incidents, ES cost, schema health, query coverage) that show the impact of your roadmap
• Work at the heart of Iterable’s data plane—where decisions about ingestion, storage, schema, and queries shape everything built on top of it
• Make concrete tradeoffs between flexibility and guardrails: when to allow arbitrary payloads vs. when to insist on structure, how much history to keep online, and which queries are too risky to run
• Partner closely with senior engineering leaders on long-horizon decisions about search/index strategy, user stores, SLOs, and cost posture
• Spend time with customers’ data and engineering teams to understand how they actually model users and events today—and reflect that reality in a cleaner, more powerful user data platform