We’re looking for a Product Owner to join our Platform product team, owning the GeoInt layer that provides the geographic foundation of our maritime intelligence platform. This layer covers the basemaps users see, the system polygons that define the world’s maritime geography (countries, EEZs, territorial waters), ports / terminals / docks, and underwater infrastructure — including time-aware features that change as the seafloor and infrastructure evolve.

This is an engineering-heavy product role. Your center of gravity will be partnering closely with engineering on the pipelines, data models, and serving infrastructure that turn raw geospatial sources into a coherent, performant, queryable geo layer for the rest of the product to build on. You’ll work alongside adjacent product owners (vessel positional data, activities, risk) to make sure GeoInt integrates cleanly into the workflows they rely on.

What you’ll do?

• Own the product vision, roadmap, and backlog for the GeoInt layer — basemaps, system polygons (countries, EEZs, territorial waters), ports / terminals / docks, and underwater infrastructure.
• Develop deep expertise in the underlying geo data sources: providers, formats, accuracy, refresh cadence, licensing, and the temporal aspects of features that change over time.
• Partner closely with engineering on geo data pipelines, ingestion, normalization, spatial indexing, tile serving, and how the GeoInt layer is exposed to other products and to end users.
• Define and track data-quality and coverage metrics (positional accuracy, completeness by region, freshness, licensing posture) and use them to drive prioritization.
• Coordinate with other product owners — vessel positional data, activities, risk — to ensure GeoInt integrates cleanly into the layers built on top of it.
• Translate customer feedback, analyst workflows, and internal stakeholder input into clear, prioritized user stories and acceptance criteria, including support for user-defined polygons where relevant.
• Communicate roadmap, progress, data-quality posture, and trade-offs clearly to stakeholders across product, go-to-market, and leadership.
• Partner with engineering day-to-day — sprint planning, backlog grooming, and trade-off decisions on scope, quality, and timing.