Product Owner (Data Platform)

The Product Owner is the in-team product orchestrator for the enterprise data platform — accountable for backlog grooming, sprint planning, capability roadmap, gate criteria, and partnership with platform consumers (AI / agent platforms, business-unit data teams, data scientists). The role translates consumer needs into platform stories with measurable acceptance criteria and runs the cadence that ships platform capability with API contracts, SDKs, and governance baked in.

Key Responsibilities

• Own the platform backlog in the team's Jira project — story creation, refinement, prioritisation, acceptance criteria; maintain the platform capability roadmap in partnership with engineering leadership.
• Translate platform-consumer needs (AI / agent platforms, business-unit data teams, data scientists) into engineering stories with measurable acceptance criteria.
• Run sprint planning, review, and retrospective every two weeks for the platform team; maintain velocity tracking and scope discipline.
• Author gate criteria for platform services in partnership with the Tech Leads and engineers — service-level objectives, API contract maturity, SDK readiness, governance evidence; co-chair platform-capability reviews.
• Drive service-contract negotiations between the platform team and its consumers — knowledge graph, LLM gateway, vector search, model registry, data product catalogue — with documented SLOs, versioning, and deprecation policies.
• Track platform KPIs — capability adoption, service-level objective compliance, cost reduction, governance gate closure rates — and report monthly to platform leadership.
• Coordinate cross-team dependencies with peer-platform organisations, governance, security, and finance functions; resolve scope-overlap escalations.
• Maintain the platform risk register and surface escalations on a documented cadence.

Requirements

• Bachelor's or Master's degree in Computer Science, Business, Engineering, or a related discipline.
• 5+ years product management / ownership with technical-product track record.
• Platform-as-product or API / SDK product delivery — has shipped products consumed by other engineering teams (not end-user products only).
• Backlog ownership at scale — Jira (or comparable) with multi-team coordination.
• Sprint cadence and agile rituals — planning, review, retro, story breakdown.
• Stakeholder management with parallel accountability (engineering leadership + consumer teams) without friction.
• SLO-driven product decisions — has shipped platform services where measurable service objectives gate releases.
• Data-infrastructure or cloud-platform literacy; technical product fluency.