Product Manager (Data Platform & AI Platform)
Role Overview
Define strategy and drive delivery of data, analytics, and AI capabilities across a data platform and a customer-facing AI platform.
Own platform vision, roadmap, and execution, working with engineering teams and shaping AI-driven customer experiences.
Key Skills for This Role
Full Job Posting
About the role
Define strategy and drive delivery of data, analytics, and AI capabilities across a data platform and a customer-facing AI platform.
Own platform vision, roadmap, and execution, working with engineering teams and shaping AI-driven customer experiences.
About Tecsys
Tecsys provides supply-chain solutions to healthcare systems, hospitals, pharmacies, distributors, retailers, and third-party logistics providers.
The company describes its work environment as digital-first, with offices and collaborative workspaces; no specific remote or hybrid schedule is stated.
Responsibilities
- Define and execute product strategy and roadmaps across data and AI platform domains.
- Own data ingestion, streaming, transformation, integration, and analytics capabilities.
- Lead data quality, governance, security, observability, and scalability direction.
- Partner with engineering, architecture, and cross-functional teams to translate business needs into technical solutions.
- Own delivery of customer-facing AI assistants, workflows, and intelligent tools.
- Translate customer needs into scalable AI product experiences; gather feedback, measure adoption, and iterate.
- Manage backlogs, prioritize work, write user stories, and support Agile delivery.
- Conduct market research and competitive analysis; define success metrics and KPIs.
- Contribute to go-to-market planning, communicate product vision, and balance near-term delivery with long-term investments.
Qualifications
- At least 3 years of product management or similar experience in a technical software environment.
- Strong understanding of data platforms, including pipelines, streaming, integration, modeling, governance, and analytics.
- Experience with modern cloud data ecosystems; Databricks and AWS are preferred.
- Familiarity with AI/ML product concepts, especially customer-facing copilots or intelligent workflows.
- Ability to translate customer needs into product requirements, roadmaps, and deliverables.
- Hands-on backlog management and close collaboration with engineering teams in Agile environments.
- Strong communication, stakeholder management, collaboration, analytical, and problem-solving skills.
- Track record of delivering products or features end to end.
Application notes
- Applicants must be Canadian citizens, permanent residents, or hold a valid Canadian work permit.
- The employer states that human reviewers assess applications and that interview assessments should represent candidates' own work.
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