Director of Product Management – Data Intelligence

November 13

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HiveMQ

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Internet of Things • Telecommunications • Enterprise

HiveMQ is a leading enterprise MQTT platform, designed to connect, communicate, and control IoT data efficiently and reliably in real-world settings. The platform extends the power of MQTT, an industry standard for IoT messaging, by providing a robust solution for production IoT deployments. HiveMQ offers flexible integration options, enterprise-grade security, and can be deployed on-premise or in the cloud. It supports various use cases across industries such as automotive, energy, transportation, and smart manufacturing, and is compliant with SOC2 and ISO/IEC 27001 standards. HiveMQ is also actively involved in advancing the adoption of MQTT through leadership roles in several technical committees and open source projects.

51 - 200 employees

Founded 2012

📡 Telecommunications

🏢 Enterprise

💰 Series A on 2022-05

📋 Description

• Define and drive product strategy for the Data Intelligence portfolio, focusing on context/governance, data modeling for decision-making, real-time insights, and AI-driven actions. • Lead 0-to-1 product initiatives from conception through market success, leveraging your proven experience launching new data intelligence and analytics products. • Bridge the gap between raw data streams and intelligent action—envision how customers will model, contextualize, and govern their data to unlock business value. • Champion AI enablement: drive product capabilities that make IoT data AI-ready for predictive analytics, automated decision-making, and intelligent actions. • Establish clear, inspiring vision for your teams derived from company strategy, helping prioritize and reprioritize for organizational success. • Think cross-functionally and ahead: understand how data intelligence connects to GTM, our revenue model, and anticipate the evolution of data governance, context management, and AI-driven automation. • Drive measurable business outcomes across adoption, usage, revenue, and customer satisfaction metrics for your product portfolio. • Own the data story: work with product data analysts to instrument products effectively, measure impact, and report progress toward business objectives. • Communicate value effectively through data-backed storytelling to executives, customers, and cross-functional stakeholders. • Identify and address organizational bottlenecks, proposing process improvements as business scale demands. • Make hard calls: determine when products or features should be terminated if they don't deliver desired outcomes. • Partner deeply with R&D leadership (Team Leads, Directors) to ensure technical feasibility and delivery excellence. • Collaborate with GTM organizations including Sales, Customer Success/Support, Alliances, and Product Marketing at director and VP levels. • Manage strategic customer relationships and handle escalations with appropriate oversight. • Build consensus across departments on complex, cross-functional initiatives. • Develop & present roadmaps and proposals to senior leadership, occasionally engaging with C-suite executives. • Maintain intimate customer knowledge through ongoing strategic customer relationships. • Advocate for customer needs by framing capabilities in terms of customer outcomes and business priorities. • Validate product-market fit through continuous discovery and customer feedback loops. • Drive customer intimacy beyond strategic accounts to understand broader market needs.

🎯 Requirements

• 8-15 years total work experience, with significant portion in product management or consulting • 4+ years of people management experience, including leading distributed teams across geographies and time zones • Proven 0-to-1 success: At least two successful new product launches from conception to market success in the data and analytics domain • Data-driven product development: demonstrated success using quantitative and qualitative methods to drive product decisions • Budget and resource management: experience allocating resources across teams and managing to budget. • Domain Expertise (Highly Valued): • Data intelligence and contextualization: understanding of how to add semantic meaning, business context, and governance to streaming data. • Data modeling for decision-making: experience building products that enable customers to model data in ways that drive automated decisions and actions. • Real-time analytics and insights: proven track record with streaming analytics, complex event processing, or real-time intelligence platforms. • AI/ML integration: familiarity with how data preparation, feature engineering, and data quality impact AI model effectiveness and AI-driven automation. • Data governance and compliance: understanding of data lineage, quality, privacy, and regulatory requirements (GDPR, industry-specific mandates). • Data streaming and movement technologies: hands-on experience with Kafka, TIBCO, MQTT, or similar distributed streaming platforms. • ETL and data integration: familiarity with tools like Talend, GoldenGate, Informatica, or similar data transformation technologies. • Distributed systems: deep appreciation for reliability, scalability, and performance at scale. • IoT and edge computing: understanding of operational technology (OT) and information technology (IT) convergence.

🏖️ Benefits

• Health insurance • 401(k) matching • Flexible work hours • Paid time off • Remote work options