The Role
A Data Product Manager is responsible for defining, building, and managing data-driven products that deliver business value. This role bridges the gap between business stakeholders, data engineering, analytics teams, and end users to ensure data products are reliable, scalable, and aligned with strategic goals.
Your responsibilities:
1. Product Strategy & Roadmap
- Define the vision, strategy, and roadmap for data products (e.g., dashboards, data platforms, APIs, ML models).
- Identify opportunities to leverage data for business growth and operational efficiency.
- Translate business requirements into actionable product features and user stories.
2. Stakeholder Management
- Collaborate with business leaders, analysts, engineers, and data scientists.
- Act as the primary point of contact for data product requirements and prioritization.
- Communicate product updates, progress, and outcomes to stakeholders.
3. Data Product Development
- Work closely with data engineers and architects to design scalable data solutions.
- Ensure proper data modelling, governance, and quality standards.
- Oversee the end-to-end lifecycle of data products (concept → development → deployment → optimization).
4. Analytics & Insights
- Define KPIs and success metrics for data products.
- Drive data-driven decision-making across the organization.
- Ensure actionable insights are delivered through dashboards, reports, or advanced analytics.
5. Agile Delivery
- Manage backlog, prioritization, and sprint planning.
- Write clear user stories and acceptance criteria.
- Ensure timely and high-quality delivery of features.
6. Data Governance & Compliance
- Ensure data privacy, security, and regulatory compliance (e.g., GDPR).
- Define data ownership, standards, and quality controls.
7. User Experience & Adoption
- Understand user needs and pain points.
- Drive adoption through training, documentation, and usability improvements.
- Gather feedback and continuously improve data products.
Your Profile
- Strong product management experience (ideally in data or analytics products)
- Solid understanding of:
- Data architecture and pipelines (ETL/ELT)
- Data warehousing (e.g., Snowflake, Azure Synapse, Big Query)
- BI tools (Power BI, Tableau, Looker)
- Knowledge of SQL and data querying (hands-on or conceptual)
- Familiarity with Agile/Scrum methodologies
- Excellent stakeholder management and communication skills
…
