1. Agile Delivery for Data Products
.Facilitate agile ceremonies (sprint planning, stand-ups, reviews, retrospectives) for data product teams.
.Support consistent execution of data product backlogs aligned to agreed roadmaps and enterprise priorities.
.Help teams plan, sequence, and deliver data assets incrementally and predictably.
.Ensure visibility into delivery progress, risks, dependencies, and impediments.
2. Partnership with Data Product Managers
.Work closely with Data Product Managers to support backlog readiness, sprint goals, and delivery cadence.
.Help translate product roadmaps into executable sprint plans without owning prioritization decisions.
.Provide delivery insights such as capacity, throughput, and dependency risks to inform planning.
.Support product reviews and stakeholder updates with execution-focused perspectives.
3. Team Coaching & Continuous Improvement
.Coach data engineering, analytics, and platform teams on agile and lean delivery practices in a data context.
.Identify process, coordination, or dependency issues impacting delivery effectiveness.
.Facilitate retrospectives that drive practical improvements in flow, quality, and collaboration.
.Encourage accountability, transparency, and shared ownership within delivery teams.
4. Dependency & Stakeholder Management
.Coordinate across data engineering, analytics, governance, platform, and upstream/downstream teams.
.Help manage interdependencies across data domains, pipelines, and shared platforms.
.Proactively surface delivery risks, delays, or conflicts to Product Managers and leadership.
.Support alignment between delivery timelines and enterprise data priorities.
5. Metrics, Reporting & Delivery Insights
.Track delivery metrics such as sprint predictability, throughput, flow efficiency, and stability.
.Provide insights into delivery health, bottlenecks, and maturity trends.
.Ensure metrics are used to enable transparency and improvement-not enforcement.
.Contribute to leadership reporting with objective views of delivery performance.
6. Data Ways of Working & Maturity
.Support adoption of consistent agile delivery practices across data product teams.
.Adapt agile practices to suit data engineering and analytics realities (dependencies, quality checks, platform work).
.Collaborate with other Scrum Masters and delivery leads to strengthen enterprise data delivery maturity.
.Promote pragmatic agility over rigid frameworks.