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 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
Preferred Experience
- 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
EOE Statement:
Datacor is an Equal Opportunity Employer and does not discriminate on the basis or race, color, religion, sex, national origin, age, disability, veteran status, or any other protected characteristic.
Use of AI During Interviews:
At Datacor, we value thoughtful problem-solving and authentic perspectives. To ensure a fair and consistent evaluation process, we ask that candidates do not use generative AI tools or outside assistance during live interviews unless explicitly stated otherwise. We're interested in hearing your experience, your approach, and how you think through challenges.
Top Skills
Similar Jobs
What you need to know about the San Francisco Tech Scene
Key Facts About San Francisco Tech
- Number of Tech Workers: 365,500; 13.9% of overall workforce (2024 CompTIA survey)
- Major Tech Employers: Google, Apple, Salesforce, Meta
- Key Industries: Artificial intelligence, cloud computing, fintech, consumer technology, software
- Funding Landscape: $50.5 billion in venture capital funding in 2024 (Pitchbook)
- Notable Investors: Sequoia Capital, Andreessen Horowitz, Bessemer Venture Partners, Greylock Partners, Khosla Ventures, Kleiner Perkins
- Research Centers and Universities: Stanford University; University of California, Berkeley; University of San Francisco; Santa Clara University; Ames Research Center; Center for AI Safety; California Institute for Regenerative Medicine
