Director, Product Management
New
CanadaFull-TimeDirector
Salary not disclosed
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Job Details
- Experience
- 10+ years
- Required Skills
- Product ManagementSaaSLangChain
Requirements
- 10+ years of product management or platform leadership experience in SaaS, data platforms, or enterprise software environments.
- Proven experience leading data-intensive products such as analytics platforms, observability systems, or large-scale data ecosystems.
- Strong background in enterprise data systems including big data, data warehousing, and real-time streaming architectures.
- Working knowledge of modern AI and data technologies such as vector databases (e.g., pgVector), semantic data models, and AI orchestration frameworks (e.g., LangChain).
- Demonstrated ability to lead cross-functional teams and influence senior stakeholders across product, engineering, and GTM functions.
- Strong business acumen with experience in P&L impact, revenue drivers, product adoption metrics, and long-range strategic planning.
- Experience operating in AI-enabled or rapidly evolving product environments with a strong ability to drive organizational change.
- Excellent communication and leadership skills, with the ability to translate complex technical concepts into clear business outcomes.
Responsibilities
- Own the enterprise data product roadmap, including the Core Data Layer strategy and long-term architecture for unified, intelligent data systems.
- Lead the consolidation and normalization of fragmented data sources into a semantic, AI-ready intelligence layer for cross-functional and executive use.
- Partner with GTM and business leaders to translate data into actionable insights that improve customer outcomes, account growth, and revenue performance.
- Drive the evolution toward an AI-native product development lifecycle, embedding automation and intelligent workflows into data product delivery.
- Oversee enterprise observability strategy, ensuring visibility into system performance, data quality, and operational efficiency metrics.
- Establish and enforce governance frameworks, including data privacy, PII protection, and secure-by-design principles across all data assets.
- Collaborate with engineering and executive teams to ensure data initiatives align with financial, operational, and strategic business goals.
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