Senior Data Product Manager
New
E
EverfiEdTech
United StatesFull-TimeSenior
Salary$130,000- $150,000 annual base salary
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Job Details
- Experience
- At least 5 years of product management experience, with at least 2 years specifically in data products, analytics platforms, or data-intensive SaaS environments
- Required Skills
- SQLAgileMicrosoft Power BIProduct ManagementTableauSaaSLooker
Requirements
- Bachelor's degree in Computer Science, Data Science, Business, Education Technology, or related field.
- Minimum 5 years of product management experience, including 2+ years in data products, analytics platforms, or data-intensive SaaS.
- Experience with Agile development methodologies and managing engineering backlogs.
- Proficiency working with data sets, data pipelines, and data visualization tools (e.g., Tableau, Looker, Power BI).
- Familiarity with cloud data infrastructure (AWS, Azure, GCP), data warehousing, and API-based product architectures.
- Working understanding of AI/ML concepts applied to product features.
- Proficiency with SQL or equivalent querying tools for working on schema design and data contracts.
- Ability to build product narratives, gap analyses, and use cases connecting decisions to business outcomes.
- Experience in B2B or B2B2C EdTech, HRTech, or enterprise SaaS environments (preferred).
Responsibilities
- Own and maintain the product roadmap and backlog for data product areas such as learner analytics and outcomes reporting.
- Prioritize features and enhancements based on customer value, business impact, and technical feasibility.
- Manage sprint planning, release coordination, and post-launch measurement with engineering leads.
- Conduct user research and competitive analysis to inform product requirements and user stories.
- Coordinate cross-functionally across platform engineering, data science, and UX throughout the product lifecycle.
- Define data platform features that serve both external customers and internal operational needs.
- Champion data quality, integrity, and privacy compliance across all product areas.
- Identify and implement opportunities to incorporate AI and machine learning into product features.
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