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описание
Intermedia Intelligent Communications provides unified communications, contact center, AI, messaging, analytics, and related services. Its Data Hub brings together data from products and systems for analytics, reporting, APIs, and AI-driven use cases.
задачи
Own the product strategy and roadmap for the Data Hub and shared analytics data foundation;
Partner with Product Managers and Engineering teams across UC/PBX, Contact Center, AI, messaging, and other domains to define and prioritize the roadmap;
Establish and drive adoption of common patterns and best practices for product instrumentation, event generation, data contracts, ingestion, and access;
Partner with Data and Engineering architects to define and evolve common data models;
Ensure data from different products can be consistently connected and analyzed across domains, channels, and customer journeys;
Define requirements for exposing trusted data to downstream consumers through APIs, analytics tools, embedded experiences, AI applications, and other access patterns;
Make it easier for product and engineering teams to onboard data and build on the shared foundation;
Balance migration of existing and legacy data flows with new product requirements;
Identify common needs across product teams and prioritize shared platform capabilities;
Define and track success measures for Data Hub adoption, data availability, quality, timeliness, platform utilization, and analytics enablement effort;
Ensure the data foundation supports emerging AI use cases, including AI Agents, Interaction Insights, prompt-based analytics, and other AI-driven experiences;
Work with the Principal Product Manager for Product Analytics and the cross-product Analytics SME community to align Data Hub priorities with customer, partner, and product needs.
требования
5+ Years of Product Management experience, including meaningful experience with data platforms, analytics platforms, developer platforms, or technically complex B2B SaaS products;
Strong understanding of event-driven architectures, data ingestion and pipelines, data contracts, data modeling, APIs, data quality, and semantic/business models;
Ability to engage deeply with Data and Engineering teams, understand technical trade-offs, challenge design decisions, and maintain focus on product and business outcomes;
Experience building shared platforms used by multiple product or engineering teams, with an understanding of platform-as-a-product principles;
Experience translating needs across multiple product domains into reusable platform capabilities;
Proven ability to influence and align multiple teams without direct authority and drive adoption of common standards and practices;
Strong prioritization skills and ability to balance foundational platform investments, migration and technical debt, and immediate customer-facing needs;
Excellent written and verbal communication skills, with the ability to translate complex data architecture and platform concepts into clear product and business narratives;
Nice to have: Experience with Snowflake or similar modern cloud data platforms, Kafka, EventHub, or other event-driven architectures, Contact Center (CCaaS), Unified Communications (UCaaS), or communications platforms, real-time and historical analytics, AI/ML products, and modernization of legacy analytics or data architectures.
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