You have built and shipped enterprise B2B SaaS products or platforms used by multiple teams or product surfaces
Fluency with technical concepts including data modeling, schemas, APIs, event systems, distributed systems, data pipelines, warehouses, or analytics infrastructure
Hold your own in architecture and technical design discussions with senior engineers and data practitioners
You have made consequential build-vs-buy, abstraction, architecture, reliability, or scalability trade-offs
Translate complex technical capabilities into clear product requirements and platform interfaces that engineers can build from
You have delivered ambiguous, cross-functional programs where alignment and influence mattered more than organizational authority
Fluent in quantitative reasoning and can define metrics that demonstrate whether a platform investment is actually creating value
Understand enterprise expectations around security, permissions, privacy, governance, compliance, and reliability
Experience with geospatial data, imagery, remote sensing, computer vision, or asset inspection platforms
Experience with high-volume or complex data processing systems
Experience defining domain models or shared data architectures across multiple products
Experience building platforms that support machine learning, generative AI, or agent-based systems
Experience with data lineage, observability, governance, or master-data concepts
Experience working with operational systems where digital workflows connect to physical-world activity
What the job involves
Build the platform that powers every Zeitview product
Own the core data model and shared platform services that enable data capture, processing, analysis, and delivery across Zeitview’s products and verticals
Define how domain objects and large-scale geospatial, imagery, inspection, and operational datasets are represented, connected, processed, governed, and exposed to applications, customers, and AI systems
This is a technical, high-leverage product role for someone who cares about building reliable, scalable, extensible systems
You’ll work closely with product engineering, data engineering, data science, security, and product teams to turn fragmented systems and data into durable platform primitives that teams can build on with confidence
Own the roadmap for shared platform services and data capabilities
Work across product teams to understand platform needs, unblock high-value use cases, and drive consistency without unnecessarily constraining product innovation
Maintain a clear understanding of the domain model, datasets, services, APIs, and platform dependencies
Prioritize and make trade-offs legible to engineering, product, and leadership
Partner with engineering to build reliable, scalable APIs, services, pipelines, and interfaces that turn complex underlying systems into simple platform capabilities
Define canonical entities, relationships, contracts, events, permissions, and semantics used across the data lifecycle
Improve how application teams discover, understand, and consume shared capabilities
Define standards for data quality, lineage, governance, discoverability, documentation, reliability, and developer experience
Identify where shared capabilities should be standardized at the platform layer versus owned within individual products or verticals
Evaluate how AI and agent-based systems should interact with Zeitview’s data and platform capabilities, including the primitives required to make those systems reliable and scalable
Define success metrics for platform investments and measure adoption, reliability, reuse, and business impact