Senior Lead Product Manager, Data Platform & Analytics
DatacorRemote, USPosted 21 March 2026
Tech Stack
Job Description
About Us:
Datacor
is the leading provider of software solutions, including ERP, CRM, Asset Tracking, Simulation and Formulation, to the process manufacturing space. We are on a mission to better equip the industry with software solutions and move it forward by building thoughtful, intuitive products that solve our
customers’
most difficult problems.
We are passionate about serving our customers and helping them use data as a competitive advantage. Our customers make products that extend and sustain lives by sanitizing, fertilizing, beautifying, cleaning, and recycling the world we live in. We at
Datacor
help our customers make those products you use every day more safely, cost effectively and more efficiently through our technology platforms and applications.
The Role:
Datacor is modernizing how process manufacturers operate by unifying data across ERP, MES, WMS, formulation, quality, logistics, and engineering systems—and turning that data into actionable insights, predictive intelligence, and scalable analytics products.
We are hiring a Senior Product Manager, Data Platform Analytics to own the strategy, roadmap, and commercialization of Datacor’s data lake and analytics platform across all Datacor business units and products.
This role is responsible for transforming fragmented product data into a single, governed, multi-tenant data platform that supports embedded analytics, premium analytics products, data lake as a service, and AI/ML-powered forecasting and predictive use cases for process manufacturers.
This is a high-impact, cross-cutting role that requires strong platform instincts, commercial thinking, and the ability to drive alignment across product teams without direct authority .
Responsibilities:
Product Vision Strategy:
Define and evolve Datacor’s data platform and analytics strategy across all product lines, balancing short-term customer value with long-term platform scalability.
Establish a clear analytics and data roadmap that supports:
Embedded analytics
Advanced analytics and dashboards
Data Lake as a Service (DLaaS)
Predictive and forecasting use cases powered by AI/ML
Ensure AI and machine learning capabilities are built on a strong, reliable data foundation, not treated as standalone features.
Data Platform Analytics Productization:
Data ingestion from across multiple products
Standardized schemas, data contracts, and semantic layers
Scalable, multi-tenant analytics architecture
Deliver customer-facing analytics products, including role-based dashboards and self-service analytics tools
Launch point solutions using the data lake (e.g., forecasting, variance analysis, operational benchmarking).
Commercial Ownership Go-to-Market:
Own packaging, pricing, and monetization strategy for:
Embedded analytics
Premium analytics products
Data Lake as a Service
AI-enabled forecasting and predictive analytics
Develop business cases, ROI models, and success metrics for analytics and data products.
Partner with Sales, Marketing, and Customer Success to:
Define value propositions
Enable demos and sales motions
Drive adoption and expansion
Cross-Business Unit Leadership:
Work across all Datacor product teams to align data ingestion, schemas, and priorities.
Own cross-BU data decisions, balancing local product needs with platform consistency and scalability.
Establish and enforce data contracts to prevent customer-specific logic from leaking into the shared platform.
Customer Market Discovery:
Engage directly with customers to understand analytics needs across manufacturing, quality, supply chain, finance, and engineering.
Identify high-value manufacturing use cases such as:
Forecasting and demand planning
Yield and variance analysis
Predictive maintenance indicators
Inventory and throughput optimization
Track trends in manufacturing analytics, industrial AI, and data platforms to guide investment decisions.
Qualifications:
Required Experience:
5+ years of product manage ... (truncated, view full listing at source)
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