Technical Program Manager III, Learning and Development, Google Cloud

Job description

Lead the programmatic scoping and scaling of technical enablement telemetry and learning evaluation, data footprints, and automated capability analytics. Architect and manage robust quantitative engineering validation data pipelines to measure knowledge transfer efficacy across the workforce. Define data environment psychological constructs and cognitive load metrics, establishing precise system health goals with engineering leads. Translate proficiency telemetry into concrete feature requests, system schemas, and technical specifications for enablement platform developers. Own end-to-end instrumentation design for technical evaluations and automated data collection pipelines. Oversee system experimentation frameworks to evaluate enablement infrastructure efficacy and knowledge transfer models. Drive cross-functional alignments with technical leads to implement the AI Competency matrix and proficiency validation models globally. Establish data quality gates and validation models to guarantee the integrity and reliability of technical platform metrics. Minimum Qualifications: Bachelor's degree or equivalent practical experience. 5 years of experience in program or project management. Experience with learning and development or learning systems. Experience in technical enablement and data analytics. Preferred Qualifications: Master's degree or PhD in Learning Psychology, Cognitive Science, or Data Science with a focus on quantitative validation and evaluation architectures. 5 years of experience managing cross-functional or cross-team projects. Experience in psychometric validation and evaluation architectures used to guarantee the integrity and reliability of technical capability benchmarks. Experience in applying advanced behavioral data modeling or cognitive load frameworks to software platform interactions and technical competency definitions. Practical familiarity with cloud infrastructure environments and the integration of AI tools into technical enablement pipelines.