Engineer Strategy Program Manager, Commercial Personal Systems

Engineer Strategy Program Manager, Commercial Personal Systems

Description -

Job Summary

The Engineering Strategy Program Manager drives data-informed decisions across global Engineering. This role leads strategic analysis, workforce and budget planning, portfolio prioritization, and AI-enabled transformation initiatives.

Partnering with engineering, product, finance, and HR leaders, the Expert develops clear recommendations, planning models, and executive-ready insights that align resources, investments, and organizational capabilities with business priorities.

Responsibilities

• •Lead end-to-end strategic analyses for engineering investments, product portfolios, resource allocation, operating expenses, capital expenditures, NRE, and productivity initiatives.
• •Develop fact-based recommendations for executive decisions, including options, trade-offs, risks, financial implications, capacity impacts, and implementation considerations.
• •Build and maintain planning models for headcount, skills, workforce mix, site strategy, engineering capacity, demand forecasts, hiring plans, contractor utilization, and budget scenarios.
• •Partner with R&D, product, finance, and program leaders to establish planning assumptions, align priorities, identify gaps, and recommend actions to improve delivery confidence.
• •Translate ambiguous business questions into structured problem statements, analytical approaches, decision frameworks, and executive-ready outputs.
• •Design dashboards, scorecards, and management-review materials that provide transparent visibility into portfolio health, resource deployment, budget performance, engineering productivity, and strategic-program outcomes.
• •Lead analyses related to AI-enabled engineering transformation, including use-case prioritization, adoption measurement, productivity baselines, value realization, training needs, governance, and change-management implications.
• •Develop business cases and investment proposals for major initiatives, including benefits hypotheses, cost estimates, sensitivity analyses, risk assessments, milestone plans, and success metrics.
• •Define and improve planning processes, analytical standards, data definitions, governance mechanisms, and reporting rhythms across globally distributed engineering organizations.
• •Influence senior stakeholders through concise executive storytelling, clear data visualization, and practical recommendations that balance strategic ambition with implementation realities.
• •Mentor analysts and senior analysts in structured problem solving, financial and operational modeling, executive communication, data quality, and stakeholder management.
• •Serve as a recognized subject-matter expert in one or more areas such as R&D planning, engineering economics, AI transformation, workforce strategy, portfolio management, operating-model design, or data-driven executive decision support.

Education & Experience Recommended

• •Four-year or Graduate Degree in Business Administration, Statistics, MIS, or any other related discipline or commensurate work experience or demonstrated competence.
• •Typically has 7-10 years of relevant experience in engineering strategy, R&D planning, business operations, product strategy, management consulting, finance, program management, technical operations, or a comparable analytical leadership role.
• •Demonstrated experience supporting decisions in a complex technology, engineering, hardware, software, semiconductor, platform, manufacturing, or product-development environment.
• •Expert-level ability to structure ambiguous problems, formulate hypotheses, analyze evidence, identify root causes, and develop actionable recommendations.
• •Strong experience with financial and operational analysis, including budget planning, investment prioritization, resource allocation, scenario modeling, cost-benefit analysis, and business-case development.
• •Demonstrated capability in workforce and capacity planning, including headcount forecasting, skills analysis, location or site strategy, hiring plans, build-buy-partner decisions, and demand-versus-capacity modeling.
• •Advanced proficiency in Excel and presentation development, including complex models, scenario analysis, executive dashboards, data visualization, and concise leadership narratives.
• •Experience using data-analysis and business-intelligence tools such as Power BI, Tableau, SQL, Python, or equivalent platforms; ability to assess data quality and establish reliable metrics.
• •Ability to communicate complex analyses clearly to executive audiences and tailor the message for technical, financial, and business stakeholders.
• •Proven ability to lead cross-functional workstreams, align stakeholders with competing priorities, and drive decisions in a global and matrixed organization.
• •Strong business judgment, intellectual curiosity, attention to detail, and comfort making recommendations despite incomplete or evolving information.
• •Professional fluency in English, including the ability to write executive pre-reads, decision memos, operating-review materials, and business cases.

• Preferred Certifications
• PMI PMP, ACP, BPA

Knowledge & Skills

• •Expert knowledge of engineering strategy, R&D planning, portfolio management, and resource-allocation methodologies.
• •Strong understanding of technology-product development environments, including hardware, software, platform, firmware/BIOS, system architecture, and global engineering execution.
• •Deep capability in business analysis, strategic problem solving, hypothesis-driven analysis, and translating ambiguous questions into structured decision frameworks.
• •Advanced expertise in financial planning and investment analysis, including OPEX, CAPEX, NRE, budget development, cost modeling, return-on-investment analysis, and scenario planning.
• •Strong knowledge of workforce planning, engineering-capacity modeling, skills forecasting, headcount planning, site strategy, hiring plans, contingent workforce strategy, and demand-versus-capacity analysis.
• •Advanced analytical and modeling skills using Excel, including complex formulas, pivots, Power Query, financial models, sensitivity analyses, forecasting models, and executive dashboards.
• •Proficiency in business-intelligence and data-analysis tools such as Power BI, Tableau, SQL, Python, or equivalent platforms for data preparation, visualization, automation, and insight generation.
• •Ability to establish data definitions, validate source-data quality, reconcile conflicting datasets, and create trusted management metrics.
• •Knowledge of portfolio prioritization frameworks, including strategic alignment, customer or business impact, technical feasibility, cost, risk, resource demand, and time-to-value.
• •Strong understanding of engineering productivity, development-cycle performance, operational metrics, delivery health, and mechanisms for identifying execution bottlenecks.
• •Working knowledge of AI transformation, generative AI, agentic AI, RAG, knowledge-management systems, AI governance, and AI-enabled engineering productivity workflows.
• •Ability to define AI use cases, build value hypotheses, establish baselines, measure adoption, evaluate realized benefits, and identify change-management needs.
• •Experience developing executive-ready business cases, including strategic rationale, alternatives, financial impact, risk assessment, decision requests, implementation roadmaps, and success measures.
• •Exceptional executive communication skills, including concise pre-reads, decision memos, operating-review materials, presentation storytelling, and data visualization.
• •Ability to communicate effectively with technical engineers, senior engineering leaders, finance partners, product managers, HR, program-management teams, procurement, and external development partners.
• •Strong stakeholder-management and influence skills, with the ability to build alignment across global, cross-functional, and matrixed organizations.
• •Know