Z
Zeitview
Staff Technical Product Manager
Skills
Data EngineeringProduct ManagementData ScienceData AnalysisMachine LearningAIProduct ManagerCompliance
1 month ago
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Important information
Salary:
$215,000 – $225,000 / year
Location:
San Francisco, CA, USA
Work mode:
Onsite
Published on:
25 September 2026
What they need
Who you are
- 8+ years of professional experience, including 5+ years in product management
- Meaningful experience owning technical platform, data, infrastructure, developer, or AI-enabling products
- 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
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