Senior Engineer, Front End Labor Data Engineering

You will drive measurable outcomes in labor productivity and annualized hour savings by implementing strategies focused on standardization, simplification, automation, and leveraging generative AI methodologies. These approaches will enable reductions in labor hours, enhance labor efficiency, shorten cycle times, and improve overall operating cadence.

Responsibilities

Program Management and Delivery

• Drive year over year improvement in FE labor productivity VAM/HC in support of the 5MORE productivity roadmap.

• Lead E2E execution and governance of FE labor productivity programs to ensure on time delivery and measurable outcomes. Standardize tools, methods, and processes across sites to enable scalable and repeatable execution aligned with enterprise goals.

• Integrate labor initiatives across AI, automation, robotics, DREAM team, and innovation programs into a cohesive execution plan. Track, validate, and report productivity benefits including labor hour reduction, VAM/HC, and annualized savings in partnership with Site’s Labor Champions & Finance team.

• Maintain and optimize the loading-based staffing (LBS) model to align staffing levels with actual workload demand.

• Provide governance support for SEAL and SWAT initiatives.

• Lead Labor SWAT initiatives to improve FE labor productivity and functional AI roadmap. Targeted actions address gaps, accelerate progress, and support overall productivity goals.

FE Network Productivity and Enablement

• Monitor labor performance metrics, identify gaps, benchmark best practices, and support performance recovery actions when needed.

• Enable cross site knowledge sharing to scale successful solutions and maximize network impact.

• Guide site and central teams to identify and prioritize productivity opportunities using AWMS workload data to convert effort into measurable time savings.

• Managing programs involving pipelines of AI, GenAI, automation, and low code solutions, including copilots, digital footprint, and workflow automation.

• Support development and execution of functional AI roadmaps across FE organizations with focus on reuse and scalability.

• Drive structured use case intake, value assessment, feasibility review, and deployment planning to ensure sustainable adoption.

Data Driven Insights and Reporting

• Develop KPI dashboards and management reporting to provide visibility into progress, adoption, and realized benefits.

• Translate data into actionable insights to support fact-based prioritization and decision making.

• Support workload forecasting, productivity baselining, and scenario modeling by coordinating requirements and validating outputs with stakeholders.