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7 часов назад

Product Manager (Data Platform)

Формат работы
remote (только Canada)/hybrid
Тип работы
fulltime
Грейд
middle
Английский
b2
Страна
Canada
Вакансия из списка Hirify.GlobalВакансия из Hirify Global, списка международных tech-компаний
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Описание вакансии

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TL;DR

Product Manager (Data Platform): Shaping the strategy for data catalogue, metadata, and data lineage capabilities within a large-scale data ecosystem with an accent on data discoverability and governance. Focus on defining platform roadmaps, evaluating build vs. buy decisions, and integrating AI/ML to automate data workflows.

Location: Must be based in Canada (specifically Toronto-based for occasional in-person collaboration)

What you will do

  • Define and own the product strategy and roadmap for data catalogue, metadata, and data lineage capabilities.
  • Identify and solve high-impact problems across data discovery, governance, trust, and usability.
  • Collaborate with engineering, design, analytics, and data science teams to deliver robust platform solutions.
  • Establish and track key success metrics, including adoption, performance, and business impact.
  • Evaluate build vs. buy vs. integration decisions for platform capabilities and external tools.
  • Integrate AI/ML trends into the evolution of data infrastructure and automation.

Requirements

  • 2+ years of Product Management experience in platform, data infrastructure, developer tools, or analytics products.
  • Technical background in Computer Science, Engineering, or equivalent experience.
  • Ability to engage deeply with engineering teams and contribute to technical discussions.
  • Strong systems thinking to connect user needs, platform architecture, and business outcomes.
  • Excellent stakeholder management skills across technical and non-technical audiences.
  • Must be based in Canada (Toronto).

Culture & Benefits

  • Flexible working model combining remote work with occasional in-person collaboration.
  • Opportunity to solve large-scale, high-impact data platform challenges.
  • Exposure to cutting-edge work in data infrastructure, governance, and AI-driven systems.
  • Collaborative environment with high autonomy and ownership.
  • Strong emphasis on learning, experimentation, and continuous improvement.

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