Director, Product Management (Intelligence, Insights and Context)

Workato•Palo Alto, CA

About The Position

Workato is pioneering a category-defining product that delivers intelligence, insights, and context across the entire automation ecosystem. We're building an AI-powered analytics platform with intelligent data virtualization that eliminates traditional data warehouses, ETL pipelines, and complex integration requirements - while providing unprecedented understanding of how your automation landscape actually works. Imagine business users asking natural language questions that span data across recipes, integrations, APIs, and connected applications - and getting instant, contextual answers. Imagine proactive AI that surfaces optimization opportunities, predicts failures, and recommends improvements across your entire automation landscape. This is the future we're building. We're seeking an exceptional Director of Product Management to lead this initiative from vision to market leadership.

Requirements

12+ years product management experience in enterprise software (analytics, BI, data platforms, or observability)
Proven track record building 0-to-1 products or creating new market categories
Deep understanding of data virtualization concepts: federated queries, semantic layers, data fabrics, virtual data warehouses
Strong knowledge of knowledge graphs, graph databases (Neo4j, Neptune), ontologies, and semantic technologies
Experience with AI/ML-powered analytics, predictive modeling, or augmented analytics products
Understanding of modern data architectures including data lakes, warehouses, and semantic layers
Technical depth to discuss data modeling, query optimization, embeddings, and RAG architectures
Exceptional ability to define bold visions and execute in ambiguous environments
Outstanding communication skills—can inspire teams and influence C-level executives

Nice To Haves

Experience in integration, iPaaS, automation, or workflow orchestration products
Background in data engineering, analytics engineering, or BI platforms
Hands-on knowledge of LLMs for analytics, natural language to SQL/queries, semantic search
Familiarity with vector databases (Pinecone, Weaviate) and embedding models
Experience with dbt, Looker, Tableau, or other modern analytics tools
Understanding of observability, AIOps, or IT operations analytics
Track record of thought leadership through speaking, writing, or industry influence
MBA or advanced degree in relevant field

Responsibilities

Define a New Category: Pioneer a revolutionary approach that delivers intelligence, insights, and context for enterprise automation through AI-powered analytics and data virtualization
Build the strategic vision and narrative that will reshape how enterprises understand and optimize their automation investments
Establish thought leadership and evangelize the category to CIOs, CDOs, and enterprise architects
Identify and partner with visionary customers who will co-create this future
Build Intelligence, Insights & Context Capabilities: Lead development of intelligent analytics that proactively surface insights, anomalies, predictions, and optimization opportunities across automation workflows
Design data virtualization layers that enable real-time insights across disparate data sources without data movement or replication
Architect comprehensive knowledge graphs that provide rich context by mapping relationships between recipes, integrations, applications, data flows, users, and business processes
Build semantic understanding that translates business questions into federated queries across the Workato platform and connected systems
Create natural language interfaces for conversational data exploration and analysis
Develop predictive analytics for recipe performance, failure prediction, and capacity planning
Design the Context and Data Foundation: Build the underlying data infrastructure including semantic layers, metadata catalogs, and ontologies
Design federated query engines that intelligently combine real-time and historical data
Create entity resolution and data harmonization capabilities across heterogeneous sources
Implement data lineage tracking and impact analysis for automation dependencies
Establish data governance frameworks that ensure privacy, security, and compliance
Develop embedding and vector search capabilities for semantic data discovery
Drive Product Execution: Own the product roadmap from 0-to-1 through scaling, shipping MVPs that validate category potential
Partner with Data Engineering, ML Engineering, and Platform teams to build production-grade systems
Work with Security and Compliance teams to ensure robust access controls and governance
Collaborate with Product Marketing, Sales, and Customer Success to achieve product-market fit
Define success metrics including insight accuracy, query performance, user adoption, and business value
Drive continuous innovation through experimentation and customer feedback