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Senior Product Manager – Sales & Support Analytics

Senior Product Manager – Sales & Support Analytics

CompanyFivetran
LocationToronto, ON, Canada
Salary$Not Provided – $Not Provided
TypeFull-Time
Degrees
Experience LevelSenior

Requirements

  • Great data design excites you!
  • Proven track record of shipping data products that deliver measurable results.
  • Proven ability to develop deep customer empathy and articulate customer problems.
  • Demonstrated experience using data and analytical abilities to help solve problems and make decisions.
  • Demonstrated experience performing deep data analyses for your product area.
  • Demonstrated ability to effectively collaborate with a talented team of engineers and designers.
  • Excellent written and verbal interpersonal skills with a confirmed ability to influence partners.
  • High technical and analytical acumen.

Responsibilities

  • Manage a portfolio of products and contribute to strategic decisions on growing and improving that portfolio, including optimizing revenue.
  • Build the vision, strategy and roadmap for the Sales & Support use case.
  • Learn what questions analysts are trying to answer, decide what data sources they need and design great data schemas to drive analytical success.
  • Ensure we prioritize the most important product improvements.
  • Collaborate with analytics to create reporting and ad hoc analysis using the data available and in collaboration with our key business partners.
  • Work directly with multiple engineering teams and our operations teams to ensure Fivetran is delivering the highest quality data possible.
  • Work closely with Technical Product Owners assigned to services in your use case to ensure correct prioritization of feature projects and product improvements in your area.
  • Your guiding metric will be the Revenue Weighted Usage of your portfolio of products.

Preferred Qualifications

  • Advanced experience with SQL.
  • Experience in product management or product ownership.
  • Experience as a data analyst, data engineer, data scientist, or software engineer.
  • Familiarity with leading user research discussions.
  • History of working in a high-growth company.