SaaS Product Manager - Electronics Procurement

Role Overview

As a Product Manager, your role involves translating customer and business needs into clear product requirements, data contracts, schemas, and measurable KPIs. You will define how downstream analytics, dashboards, and insight layers are designed to ensure data is interpretable and commercially useful. Your responsibility includes driving an AI‑first product roadmap by identifying the most valuable approach between classical ML models (regression, trees, clustering, forecasting) and GenAI approaches (embeddings, retrieval, vector search, LLM‑based reasoning).

You will collaborate with AI, data engineering, and platform teams to ensure data is structured, enriched, and reliable for these models. It is essential for you to establish and maintain data governance, lineage, quality, and trust frameworks across the platform. Leading multi‑disciplinary squads spanning Product, Data Engineering, AI, and Integrations will be part of your role as a senior product owner. Additionally, you will work closely with engineering leadership on scalability, performance, and reliability of ingestion and transformation pipelines.

Key Responsibilities:

• Translate customer and business needs into clear product requirements, data contracts, schemas, and measurable KPIs
• Define downstream analytics, dashboards, and insight layers for interpretable and commercially useful data
• Drive an AI‑first product roadmap by identifying valuable ML and GenAI approaches
• Partner with AI, data engineering, and platform teams to ensure structured, enriched, and reliable data
• Establish and maintain data governance, lineage, quality, and trust frameworks
• Lead multi‑disciplinary squads spanning Product, Data Engineering, AI, and Integrations
• Collaborate with engineering leadership on scalability, performance, and reliability of pipelines

Qualifications Required:

• 59 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, preferably enterprise‑grade
• Strong understanding of classical ML techniques and modern GenAI architectures
• Proficiency in data modelling, ETL / ELT principles, integration patterns, and modern data stacks
• Experience defining visualization layers and working with BI teams on dashboards and insight products
• Proven ability to collaborate effectively with engineering, data, and AI teams
• Strong communication skills translating technical concepts for business stakeholders
• Leadership experience in fast‑moving, high‑growth environments
• Exposure to supply chain, procurement, or industrial data products would be a plus

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Role Overview (Repeated)

As a Product Manager, your role involves translating customer and business needs into clear product requirements, data contracts, schemas, and measurable KPIs. You will define how downstream analytics, dashboards, and insight layers are designed to ensure data is interpretable and commercially useful. Your responsibility includes driving an AI‑first product roadmap by identifying the most valuable approach between classical ML models (regression, trees, clustering, forecasting) and GenAI approaches (embeddings, retrieval, vector search, LLM‑based reasoning).

You will collaborate with AI, data engineering, and platform teams to ensure data is structured, enriched, and reliable for these models. It is essential for you to establish and maintain data governance, lineage, quality, and trust frameworks across the platform. Leading multi‑disciplinary squads spanning Product, Data Engineering, AI, and Integrations will be part of your role as a senior product owner. Additionally, you will work closely with engineering leadership on scalability, performance, and reliability of ingestion and transformation pipelines.

Key Responsibilities:

• Translate customer and business needs into clear product requirements, data contracts, schemas, and measurable KPIs
• Define downstream analytics, dashboards, and insight layers for interpretable and commercially useful data
• Drive an AI‑first product roadmap by identifying valuable ML and GenAI approaches
• Partner with AI, data engineering, and platform teams to ensure structured, enriched, and reliable data
• Establish and maintain data governance, lineage, quality, and trust frameworks
• Lead multi‑disciplinary squads spanning Product, Data Engineering, AI, and Integrations
• Collaborate with engineering leadership on scalability, performance, and reliability of pipelines

Qualifications Required:

• 59 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, preferably enterprise‑grade
• Strong understanding of classical ML techniques and modern GenAI architectures
• Proficiency in data modelling, ETL / ELT principles, integration patterns, and modern data stacks
• Experience defining vi