Responsibilities:

• Translate customer and business needs into clear product requirements, data contracts, schemas, and measurable KPIs
• Define how downstream analytics, dashboards, and insight layers are designed to ensure data is interpretable and commercially useful
• Drive 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
• Partner with AI, data engineering, and platform teams to ensure data is structured, enriched, and reliable for these models
• Establish and maintain data governance, lineage, quality, and trust frameworks across the platform
• Lead multi-disciplinary squads spanning Product, Data Engineering, AI, and Integrations, operating as a senior product owner
• Work closely with engineering leadership on scalability, performance, and reliability of ingestion and transformation pipelines

Good to have:

• 5–9 years of experience in data products or data platform product roles
• Having exposure of electronics, OEMs, EMS, Semiconductors is mandatory.
• Mandatory experience building or scaling B2B SaaS products, ideally enterprise-grade
• Strong understanding of classical ML techniques and modern GenAI architectures, with clear judgement on practical application
• Solid grasp of data modelling, 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