Senior Lead Product Manager, Data Platform & Analytics

Datacor

About The Position

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.

Requirements

5+ years of product management experience in enterprise software
Proven experience launching and scaling data lake and/or analytics platforms
Strong understanding of: cloud-based data architecture, ETL/ELT pipeline, APIs and semantic modeling, role-based access control and multi-tenancy
Demonstrated ability to define pricing, packaging, and commercial strategy for platform products
Experience operating in complex, multi-product or matrixed organizations

Nice To Haves

Experience with AWS-based data platforms (e.g., S3-based data lakes, Lake Formation, Athena, Redshift, QuickSight)
Background in process manufacturing, industrial software, or B2B SaaS
Experience supporting self-service analytics and customer-built dashboards
Familiarity with applied AI/ML use cases in forecasting, optimization, or predictive analytics

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.