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Tier-1 employer, generalist product role, metro location, and broad technical requirements increase competition.
Role demands deep data platform, computer vision, and manufacturing domain expertise, limiting cross-industry fit.
Explicit 8+ years, mandatory data/product and computer vision experience, plus management responsibilities create strict filters.
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Own and scale robust data ingestion pipelines for structured (Oracle, SQL Server, PostgreSQL, DB2) and unstructured data (Video, Audio, PDFs, PPT) to serve enterprise needs and support the Vision Intelligence Platform.
Lead the unified Enterprise Data Platform (EDP) Console, integrating multiple data products into a single portal with features including Data Catalog, Semantic Layer, Cost Optimization, and advanced user analytics.
Define product strategy and deploy AI/ML models for the Vision Intelligence Platform to automate manual processes in recall and Field Service Action identification, enabling faster diagnosis and anomaly detection.
8+ years of experience in data product management, platform engineering, or enterprise data architecture with proven management of direct reports.
Experience managing data ingestion platforms, unified developer/data consoles, or AI/ML model deployment.
Proficient with structured database technologies (Oracle, SQL Server, PostgreSQL, DB2) and pipelines for unstructured data ingestion (Video, Audio, PDFs, Document processing).
Experience with AI-powered product management tools and incorporating AI-driven workflows into product discovery and delivery.
Experienced leader in managing enterprise-scale data platforms combining structured and unstructured data pipelines with a focus on AI/ML-based productization.
Strong background in computer vision applications, anomaly detection models, or manufacturing and quality systems, enabling impactful vision intelligence solutions.
Skilled in integrating diverse data products into unified user interfaces with a solid understanding of FinOps, cloud cost optimization, and platform analytics to drive adoption and user engagement.