Data Product Manager

6 days ago

Manila, National Capital Region, Philippines InvestEd Full time ₱1,500,000 - ₱2,500,000 per year

Responsibilities

  • Own and shape the data roadmap – translate company objectives into prioritized initiatives, balancing quick wins with foundational improvements to reduce tech/data debt
  • Gather and document requirements through structured discovery with stakeholders and translate them into clear, actionable tech specs and user stories
  • Lead and mentor a lean data team, driving clarity, accountability, and faster delivery by removing bottlenecks and improving processes
  • Plan and run sprints – manage backlog, prioritize tasks, and ensure timely delivery through lightweight but disciplined sprint planning, standups, and retros
  • Strengthen data quality and foundations – improve pipelines, models, monitoring, and documentation to ensure reliability and scalability
  • Anticipate business needs and act as the voice of data in planning sessions, aligning stakeholders and driving adoption of delivered solutions
  • Communicate progress, trade-offs, and risks clearly, keeping expectations realistic and focused on outcomes

Qualifications:

  • Bachelor's degree in Computer Science, Information Systems, Engineering, Statistics, or a related field (or equivalent practical experience)
  • At least 2 years of product management experience leading a team of at least three members or owning a product area
  • At least 5 years of cumulative experience in data analytics/analysis, data engineering, and product management
  • Proven ability to gather, document, and translate requirements into technical deliverables that drive measurable business impact
  • Skilled at prioritization, stakeholder alignment, and managing trade-offs in fast-moving environments
  • Hands-on and comfortable with ambiguity, unblocking delivery independently when needed
  • Experience with modern data stacks (dbt, Fivetran, Postgres, BigQuery/Snowflake/Redshift, BI tools) and backlog tools
  • Experience writing user stories, acceptance criteria, and technical documentation
  • Understanding of data modeling, pipelines, and data quality frameworks; comfortable going deep enough to make informed trade-offs.
  • Strong grasp of SQL and Python; ability to query data for validation and troubleshooting

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