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Product Manager, Data & Analytics

Equiti Health

Salary not specified
Sep 3, 2025
Remote, US
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Equiti is looking to shape the data experience that powers business intelligence, operational efficiency, and strategic decision-making

Requirements

  • Strong understanding of data platforms, pipelines, and governance best practices.
  • Proven ability to translate business requirements into technical specifications for data solutions.
  • Analytical mindset with experience using SQL, Python, or BI tools (Tableau, Power BI, Looker).
  • Familiarity with agile methodologies, backlog management, and tools such as JIRA or Confluence.
  • Experience in building or managing data products, preferably in SaaS or service-focused environments.
  • Ability to balance long-term data strategy with immediate operational needs.
  • Experience with data pipelines, governance frameworks, and analytics platforms.

Responsibilities

  • Lead the end-to-end product lifecycle for data products, including data pipelines, governance frameworks, and analytics platforms.
  • Translate complex data needs into clear product requirements and user stories for engineering teams.
  • Establish and maintain standards for data quality, security, governance, and compliance.
  • Partner with engineering to design and deliver scalable, reliable, and extensible data infrastructure.
  • Define and track KPIs for data usage, adoption, and business impact; iterate based on results and feedback.
  • Participate in agile ceremonies and ensure timely delivery of data-driven features and enhancements.
  • Coordinate cross-functional efforts on data integrations, reporting, and advanced analytics capabilities.

Other

  • Self-driven, highly organized, and comfortable navigating ambiguity.
  • Excellent communication and interpersonal skills for cross-functional collaboration.
  • Bachelor’s degree in Computer Science, Data Science, Business, or related field, or equivalent practical experience (minimum 3 years in a data or product role).
  • Ability to advocate for internal data users—analysts, product managers, and business stakeholders—ensuring data products are intuitive and actionable.
  • Develop product documentation, training materials, release notes, and support adoption across teams.