As an experienced candidate for the role, your responsibilities will include:
Owning the vision and roadmap across catalog, intelligence, pricing, supply visibility, lifecycle data, and integrations
Translating customer and business needs into clear product requirements, data contracts, schemas, and measurable KPIs
Defining how downstream analytics, dashboards, and insight layers are designed to ensure data is interpretable and commercially useful
Driving an AI-first product roadmap by identifying where classical ML models (regression, trees, clustering, forecasting) versus GenAI approaches (embeddings, retrieval, vector search, LLM-based reasoning) create the most value
Partnering with AI, data engineering, and platform teams to ensure data is structured, enriched, and reliable for these models
Establishing and maintaining data governance, lineage, quality, and trust frameworks across the platform
Leading multi-disciplinary squads spanning Product, Data Engineering, AI, and Integrations, operating as a senior product owner
Working closely with engineering leadership on scalability, performance, and reliability of ingestion and transformation pipelines
Qualifications required for this role are:
5-9 years of experience in data products or data platform product roles
Exposure to electronics, OEMs, EMS, Semiconductors is mandatory
Experience in building or scaling B2B SaaS products, ideally enterprise-grade
Strong understanding of classical ML techniques and modern GenAI architectures, with clear judgment on practical application
Solid grasp of data modeling, ETL / ELT principles, integration patterns, and modern data stacks
Experience defining visualization layers and working with BI teams to formulate dashboards and insight products on the platform
Proven ability to work effectively with engineering, data, and AI teams
Strong communication skills, with the ability to translate technical concepts for business stakeholders
Experience leading squads in fast-moving, high-growth environments
Exposure to supply chain, procurement, or industrial data products is a plus As an experienced candidate for the role, your responsibilities will include:
Owning the vision and roadmap across catalog, intelligence, pricing, supply visibility, lifecycle data, and integrations
Translating customer and business needs into clear product requirements, data contracts, schemas, and measurable KPIs
Defining how downstream analytics, dashboards, and insight layers are designed to ensure data is interpretable and commercially useful
Driving an AI-first product roadmap by identifying where classical ML models (regression, trees, clustering, forecasting) versus GenAI approaches (embeddings, retrieval, vector search, LLM-based reasoning) create the most value
Partnering with AI, data engineering, and platform teams to ensure data is structured, enriched, and reliable for these models
Establishing and maintaining data governance, lineage, quality, and trust frameworks across the platform
Leading multi-disciplinary squads spanning Product, Data Engineering, AI, and Integrations, operating as a senior product owner
Working closely with engineering leadership on scalability, performance, and reliability of ingestion and transformation pipelines
Qualifications required for this role are:
5-9 years of experience in data products or data platform product roles
Exposure to electronics, OEMs, EMS, Semiconductors is mandatory
Experience in building or scaling B2B SaaS products, ideally enterprise-grade
Strong understanding of classical ML techniques and modern GenAI architectures, with clear judgment on practical application
Solid grasp of data modeling, ETL / ELT principles, integration patterns, and modern data stacks
Experience defining visualization layers and working with BI teams to formulate dashboards and insight products on the platform
Proven ability to work effectively with engineering, data, and AI teams
Strong communication skills, with the ability to translate technical concepts for business stakeholders
Experience leading squads in fast-moving, high-growth environments
Exposure to supply chain, procurement, or industrial data products is a plus
