Job Description
This role leads continuous improvement initiatives through data-driven decision-making, Lean Six Sigma methodologies, and digital enablement, identifying and prioritizing opportunities to improve lead time, quality, productivity, and customer experience across complex, regulated operations.
Acting as a change agent and technical leader, the Senior Engineer drives structured problem-solving initiatives, leads cross-functional and global improvement programs, and plays a key role in embedding a culture of continuous improvement, standard work, and performance management. The role partners closely with Data & Analytics, Automation, and Business Intelligence (BI) teams to define, develop, and govern KPIs, dashboards, and advanced analytics that sustain performance and support strategic decision-making.
What you will do
Process improvement and execution:
Lead complex process improvement and standardization initiatives using Lean, Six Sigma, DMAIC, PDCA, A3, and Value Stream Mapping.
Design and facilitate workshops and Kaizen events to drive root cause analysis, waste elimination, and solution design.
Analyze large and complex operational, quality, and service datasets to identify trends, variability drivers, systemic bottlenecks, and high-impact improvement opportunities.
Define, develop, and govern KPIs related to lead time, quality, productivity, capacity, and service levels.
Partner with senior process owners and leadership to design future-state processes, standard work, and control plans.
Support validation and technology deployment activities from a process robustness and scalability perspective.
Conduct advanced structured process assessments, capability studies, control plans, and process audits.
Develop robust project plans, business cases, and executive-level summaries, clearly articulating impact on cost, capacity, service, risk, and strategic alignment.
Act as a subject matter expert (SME) in continuous improvement and operational excellence across Engineering Services.
Analytics and simulation (developing capability):
Lead or support the development and use of discrete-event simulation models to analyze flow, capacity, and variability in complex systems.
Build and validate current-state and future-state simulation scenarios in collaboration with stakeholders.
Use simulation and analytical outputs to support resource planning, automation justification, network design, and what-if scenario analysis.
Partner closely with Data & Analytics, Automation, and BI teams to design dashboards, analytics, and performance management tools that drive decision-making.
Training, coaching and capability building:
Design, prepare, and lead workshops and training sessions on: Lean Six Sigma fundamentals and advanced tools, structured problem-solving (A3, DMAIC, PDCA, Data-driven decision-making and KPI interpretation and process mapping, waste identification, and standard work
Develop high-quality training materials, templates, and case studies tailored to different audiences (engineering, operations, quality, and business teams).
Coach and mentor engineers, analysts, and process owners on continuous improvement tools and methodologies.
Support and strengthen a common continuous improvement language and mindset across teams and sites.
Serve as an internal consultant and trusted advisor for operational excellence initiatives.
What will you need:
Bachelor’s Degree in Industrial Engineering or Master’s Degree in Industrial Engineering, Modern Manufacturing Processes, or a closely related field.
Strong expertise in structured problem-solving (DMAIC, PDCA, A3), root cause analysis, statistical methods, and process capability.
Demonstrated experience leading cross-functional improvement projects with measurable impact.
Experience working with operational and quality KPIs and performing advanced data analysis.
Solid understanding of process flow, variability, capacity, and queuing concepts.
Ability to independently manage complex projects and influence without formal authority.
Ability to clearly explain technical concepts to non-technical audiences and leadership.
Prefered:
Proficiency in Excel and intermediate to advanced knowledge of Power BI or similar BI tools.
Basic knowledge or academic exposure to process simulation / discrete-event modeling (Arena, SIMUL8, FlexSim, Simio, or equivalent), with willingness to further develop this capability.
Hands-on experience with simulation tools through professional projects or advanced academic work.
Knowledge of SQL, Python, or analytical scripting.
Familiarity with automation, digital workflows, and validation processes.
Experience leading change management and continuous improvement deployment initiatives.
Demonstrated experience delivering training, workshops, or facilitation sessions.
Strong facilitation, presentation, and communication skills.
Project management or Agile certification (preferred).