Lead Product Marketing Manager, Connect AI Embedded

CData Software, Inc. is a real-time data connectivity company powering leading software platforms. They are seeking a Lead Product Marketing Manager to develop and execute a product marketing strategy for the Embedded portfolio, focusing on translating technical capabilities into clear value for product leaders.

Responsibilities:

• Develop positioning of Embedded offerings across ISV use cases—analytics, copilots/AI features, workflow/automation, and data ingestion
• Define competitive strategy against build-in-house, unified API providers, and embedded iPaaS grounded in technical accuracy
• Help lead market development for embedded connectivity in the AI era, reinforcing CData as the standard for enterprise-grade embedded data access
• Partner cross functionally to define and execute quarterly and annual GTM strategies, owning growth performance for the embedded market
• Overhaul and uplift embedded GTM presence (collateral, sales enablement tools, website) with exciting new AI-oriented visual identity and brand voice (in process, Q’1-2 timing)
• Create technical content that meets the expectations of engineering evaluators—architecture guides, implementation patterns, integration reference docs, and security explanations
• Build clear value narratives around the core pillars of Embedded: Connectivity (350+ enterprise sources), Context (feature-complete coverage), and Control (resilience to API changes, security, high-volume workloads)
• Serve as the subject-matter expert for embedded products, equipping sales, customer success, and marketing with technical messaging and differentiation
• Lead customer, market, and buyer research to inform messaging for both Tier 1 enterprise ISVs and Tier 2 high-growth SaaS teams
• Translate customer feedback and competitive insights into roadmap input—especially around coverage gaps, performance expectations, and feature needs
• Partner with product on launches for new products, features, security enhancements, and developer-tooling improvements (packaging, configuration experiences, metadata discovery, authentication flows, and test-environment support)
• Plan and execute complex marketing programs end-to-end, including product-wide release cycles and major embedded GTM programs
• Stay current on ISV, SaaS, and AI platform trends—especially how ISVs are embedding copilots, agents, and analytics that depend on deep connectivity
• Conduct first-party research with prospects, and embedded customers to refine narrative and validate value propositions
• Monitor competitive activity (unified API and embedded iPaaS providers) and develop counter-strategy position frameworks
• Track and analyze business performance metrics related to embedded engagement, opportunity development, and pipeline health
• Adopt AI tools to improve productivity and help pilot AI-driven processes across the marketing organization
• Provide mentorship to other PMMs to raise team-wide technical and strategic capability

Requirements:

• 7+ years of product marketing experience in data infrastructure, developer tools, embedded technologies, or software connectivity platforms
• Demonstrated success marketing to technical buyers—architects, engineering leads, platform teams
• Ability to produce technically credible content (architecture, security, integration guides)
• Familiarity with connectors, APIs, authentication, SQL-based interfaces (ODBC/JDBC/ADO.NET), and SaaS data landscapes
• Experience supporting complex multi-persona buying processes involving engineering evaluators and product leadership
• Strong competitive positioning skills centered on clarity and factual accuracy
• Excellent written, verbal, and presentation communication skills
• Comfortable operating autonomously in a fast-paced, high-growth environment
• Highly organized with strong attention to detail and ability to manage multi-stream initiatives
• Experience marketing to enterprise ISVs (50–10,000+ employees) or fast-growth SaaS companies
• Background in or exposure to data integration and connectivity technologies (e.g., Snowflake, Databricks, REST APIs, JDBC/ODBC)
• Cross-functional leadership and influence skills across product and engineering teams