Senior Technical Program Manager II (PMO)

Job Description

Strategic Mandate

As the Technical Program Manager (Associate) for Data & AI Platforms, you sit at the delivery interface between Nielsen's Databricks-based Data Platform and AI/Data Engineering teams and the stakeholders who build on them — internal consumers such as Finance, HR, Product, Analytics, and Data Science, as well as external partners, vendors, and clients involved in AI and Data Engineering initiatives. You understand the platform well enough to read its dependencies: Unity Catalog access gates, Delta Lake/DLT pipeline sequencing, compute and governance constraints. You translate those technical realities into program plans, risk registers, and status reporting that keep every initiative leveraging the platform moving — tracked, unblocked, and visible to leadership

Core Goals & Responsibilities

• •Technical Program Coordination: Coordinate delivery of initiatives that depend on the Databricks Lakehouse — Unity Catalog, Delta Lake, Delta Live Tables, and Databricks Workflows — translating technical dependencies, sequencing, and architecture decisions into program plans and risk registers.
• •Agile Delivery Cadence: Run Agile/Scrum or Kanban ceremonies (planning, standups, retros) across initiatives to keep delivery cadence consistent.
• •Technical Stakeholder Liaison: Partner directly with the Data Platform Lead, the Lead Data and AI Engineer, and Architecture to understand platform capabilities and constraints (compute, governance, cost), and represent them accurately to consumer stakeholders.
• •External Stakeholder & Vendor Coordination: Coordinate with external parties involved in AI and Data Engineering initiatives — technology vendors (e.g., Databricks), system integrators, data partners, and consumer stakeholders — aligning on scope, timelines, technical interfaces, and data-sharing or contractual milestones.
• •Technical Risk & Dependency Management: Maintain a technical RAID log capturing platform-level risks (e.g., Unity Catalog access blockers, compute capacity limits, governance sign-off delays) and drive resolution across engineering and business teams.
• •Release & Readiness Coordination: Coordinate technical readiness activities — environment provisioning, access/governance approvals, CI/CD release windows — for initiatives going live on the platform.
• •Technical Reporting & Governance Cadence: Translate engineering status (sprint burndown, pipeline health, platform incidents) into program-level status reports and steering committee materials that non-technical stakeholders can act on.
• •Change & Technical Adoption Support: Support rollout of new platform and AI capabilities (e.g., emerging Databricks Genie or AI features) by coordinating technical enablement sessions, documentation, and stakeholder readiness.
• •Post-Implementation Review: Facilitate post-implementation reviews and retrospectives after major rollouts, capturing lessons learned and feeding continuous-improvement actions back into the program.
• •Process & Tooling Discipline: Own PMO tooling (Jira, Confluence) configured to reflect technical workflows — epics and stories mapped to pipelines, environments, and governance gates — not just generic task tracking