Director, Product Management in Canada Creek, Nova Scotia at Jobgether

This position is posted by Jobgether on behalf of a partner company. We are currently looking for a Director, Product Management in Canada.

This is a senior leadership role shaping the future of enterprise data and AI-driven product intelligence within a fast-evolving digital experience ecosystem. The position focuses on unifying fragmented data systems into a cohesive, AI-ready architecture that powers both customer-facing innovation and internal decision-making. You will lead a centralized Data Product organization responsible for enterprise data strategy, governance, and platform observability at scale. Acting as a key partner to executive and GTM leadership, you will translate complex data assets into actionable insights and monetizable outcomes. The environment is highly collaborative, product-led, and deeply oriented toward AI-native transformation. This role requires strong strategic thinking, technical fluency, and the ability to operate at the intersection of product, data, and business impact. It is ideal for a leader who thrives in high-scale SaaS environments and enjoys driving systemic change.

In this role, you will define and execute the enterprise data and intelligence strategy, ensuring alignment between product, platform, and business objectives. You will lead the transformation of distributed data systems into a unified, semantic, AI-ready architecture that enables scalable insights and decision-making. You will also collaborate closely with GTM, engineering, and executive stakeholders to translate data into measurable business value and monetizable outcomes.

• Own the enterprise data strategy and roadmap for a unified Core Data Layer spanning product and business data
• Lead the centralization and normalization of fragmented data into a governed, semantic intelligence layer
• Partner with GTM and executive teams to convert data insights into revenue-driving and customer success outcomes
• Drive the evolution toward an AI-native product development lifecycle across data products and platforms
• Define observability frameworks and KPIs to improve data quality, system reliability, and decision effectiveness
• Establish enterprise-wide governance standards, including data security, privacy, and compliance-by-design principles
• Guide cross-functional teams in building scalable data and analytics capabilities that support strategic business growth

You bring extensive experience leading product or data organizations in complex SaaS or platform environments, with a strong blend of technical depth and strategic product leadership. You are comfortable operating at executive level while also engaging in architectural discussions around modern data systems and AI-enabled platforms. You combine business acumen with technical fluency and have a proven ability to deliver measurable impact through data-driven products.

• 5–10+ years of product leadership experience in SaaS, analytics, observability, or platform-based environments
• Proven expertise in managing large-scale data ecosystems including big data, warehousing, and real-time streaming systems
• Strong technical fluency in modern data and AI concepts such as semantic data models, vector databases, and orchestration frameworks
• Experience working in DXP, PaaS, or enterprise-grade software environments
• Demonstrated ability to lead AI-native product transformations and data-driven decision-making initiatives
• Strong business acumen with experience in P&L impact, revenue modeling, and executive-level stakeholder management
• Excellent communication and leadership skills with the ability to influence cross-functional and executive audiences

• Competitive healthcare coverage supporting employees and families
• Flexible work arrangements and generous paid time off policies
• Parental leave and family support programs
• Wellness initiatives focused on physical and mental well-being
• Employee recognition programs and career development opportunities
• Exposure to AI-native product innovation and enterprise-scale transformation